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Daedalus: A Low-Flying Spacecraft for the Exploration of the Lower Thermosphere - Ionosphere Theodoros E. Sarris1, Elsayed R. Talaat2, Minna Palmroth3, Iannis Dandouras4, Errico Armandillo5, Guram Kervalishvili6, Stephan Buchert7, David Malaspina8, Allison Jaynes9, Nikolaos Paschalidis10, 5 John Sample11, Jasper Halekas9, Stylianos Tourgaidis1, Vaios Lappas12, Mark Clilverd13, Qian Wu14, Ingmar Sandberg15, Anita Aikio16, Panagiotis Pirnaris1 1 Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, 67132, Greece 2 National Oceanic and Atmospheric Administration, Silver Spring, MD, 20910, USA 10 3 University of Helsinki, Helsinki, 00014, Finland 4 IRAP, Université de Toulouse / CNRS / UPS / CNES, Toulouse, 31028, France 5 Formerly at ESA/ESTEC, Noordwijk; now Space Engineering Consultant, The Netherlands 6 GFZ German Research Centre for Geosciences, Potsdam, 14473, Germany 7 Swedish Institute of Space Physics, Uppsala, 75121, Sweden 15 8 Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO, 80303, USA 9 University of Iowa, Iowa City, IA, 52242-1479, USA 10 NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA 11 Montana State University, Bozeman, MT, 59717-2220, USA 12 Athena Research & Innovation Centre, Amarousio Athens, 15125, Greece 20 13 British Antarctic Survey, Cambridge, CB30ET, UK 14 High Altitude Observatory, NCAR, Boulder, CO, 80307-3000, USA 15 Space Applications & Research Consultancy (SPARC), Athens, 10677, Greece 16 University of Oulu, Ionospheric Physics Unit, Oulu, 90014, Finland 25

Correspondence to: Theodore E. Sarris ([email protected])

Abstract. The Daedalus mission has been proposed to the European Space Agency (ESA) in response to the call for ideas

for the Earth Observation programme’s 10th Earth Explorer. It was selected in 2018 as one of three candidates for a Phase-0

feasibility study. The goal of the mission is to quantify the key electrodynamic processes that determine the structure and

composition of the upper atmosphere, the gateway between the Earth’s atmosphere and space. An innovative preliminary 30

mission design allows Daedalus to access electrodynamics processes down to altitudes of 150 km and below. Daedalus will

perform in-situ measurements of plasma density and temperature, ion drift, neutral density and wind, ion and neutral

composition, electric and magnetic fields and precipitating particles. These measurements will unambiguously quantify the

amount of energy deposited in the upper atmosphere during active and quiet geomagnetic times via Joule heating and

energetic particle precipitation, estimates of which currently vary by orders of magnitude between models. An innovation of 35

the Daedalus preliminary mission concept is that it includes the release of sub-satellites at low altitudes: combined with the

main spacecraft, these sub-satellites will provide multi-point measurements throughout the Lower Thermosphere-Ionosphere

Geosci. Instrum. Method. Data Syst. Discuss., https://doi.org/10.5194/gi-2019-3Manuscript under review for journal Geosci. Instrum. Method. Data Syst.Discussion started: 7 March 2019c© Author(s) 2019. CC BY 4.0 License.

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region, down to altitudes below 120 km, in the heart of the most under-explored region in the Earth’s atmosphere. This paper

describes Daedalus as originally proposed to ESA.

1 Introduction

1.1 Science Context

The Earth’s upper atmosphere, which includes the Lower Thermosphere and Ionosphere (LTI), is a complex dynamical 5

system, responsive to forcing from above and below: From above, solar radiation, solar wind and solar disturbances such as

flares, solar energetic particles and coronal mass ejections cause strong forcing through many complex processes and

produce ionization enhancements, electric fields, current systems, heating, and ion-neutral chemical changes, which are not

well quantified. From below, the LTI system is affected by atmospheric gravity waves, planetary waves and tides that

propagate through and dissipate in this region, with effects that are poorly understood. The response of the upper atmosphere 10

to global warming and its role in the Earth’s energy balance is also not well-known: whereas the increase in CO2 is expected

to result in a global rise in surface temperatures, model simulations predict that the thermosphere may cool instead (Rishbeth

and Roble, 1992), leading to thermal shrinking of the upper atmosphere; however there is disagreement about the exact

cooling trends (Qian et al., 2011; Laštovička, 2013). Quantifying the resulting secular variation in lower thermospheric

density is needed for understanding the interplay of solar and atmospheric variability, and it will be critical in the near future, 15

as increased levels of orbital debris cause increased hazards for space navigation, since lower density leads to a slower rate

of removal of objects in Low Earth Orbit (LEO) (Solomon et al., 2015). Measurements in the thermosphere are also essential

for understanding the exosphere and modelling its altitude density profile and its response to space weather events

(Zoennchen et al. 2017), as all exospheric models use parameters from this region as boundary conditions. During

geomagnetic storms and substorms, currents with increased amplitudes close through the LTI, producing enhanced Joule 20

heating (Palmroth et al., 2005; Aikio et al., 2012) and leading to significant enhancements in neutral density at high altitudes,

which results in enhanced satellite drag. Geomagnetic storms also enhance ionospheric scintillation of the Global Navigation

Satellite System (GNSS) signals, which severely degrades positional accuracy and affects the performance of radio

communications and navigation systems (Xiong et al., 2016). Sudden enhancements in the current system that closes within

the LTI induce currents on the ground, termed Geomagnetically Induced Currents (GICs); the impact of the largest of GICs 25

on power transformers in electrical power systems has, on occasions, been catastrophic and is now included in many national

risk registers as it is considered a threat to technology-based societies, should an extreme solar event occur (Pulkkinen et al.,

2017), or even repeated smaller events, which can stress transformers and reduce their operational lifetime (MacManus et al.,

2017). Despite its significance, the LTI is the least measured and understood of all atmospheric regions: In particular the

altitude range from ~100 to 200 km, where the magnetospheric current systems close and where Joule heating maximizes, is 30

too high for balloon experiments and too low for existing LEO satellites, due to significant atmospheric drag. Furthermore,

few spectral features emanate from this region; these have been exploited by recent remote-sensing spacecraft and from


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ground instrumentation, but despite these advances, this region remains under-sampled with many open questions. For

example, no data set is currently available from which the LTI energy budget can be confidently derived on a global basis.

Thus it is not surprising that scientists often informally refer to this region as the “ignorosphere”. The ever-increasing

presence of mankind in space and the importance of the behaviour of this region to multiple issues related to aerospace

technology, such as orbital calculations, vehicle re-entry, space debris lifetime etc., together with its importance in global 5

energy balance processes and in the production of GICs and GNSS scintillation make its study a pressing need.

1.2 Initial Mission Concept Overview

The target of the proposed Daedalus mission is to explore the lower thermosphere-ionosphere by performing in-situ

measurements of ion, electron and neutral temperature and density, ion drift, neutral wind, ion and neutral compositions,

electric and magnetic fields, and precipitating particles. Daedalus is composed of a primary instrumented satellite in a highly 10

elliptical, dipping polar orbit, with a perigee of 150 km, a threshold apogee above 2000 km and goal apogee above 3000 km

to ensure a sufficiently long mission lifetime, a high-inclination angle (>85o), and a number of deployable sub-satellites in

the form of CubeSats; four CubeSat sub-satellites are baselined herein, but alternative mission concepts with larger sub-

satellites shall also be discussed in the upcoming Phase-0. The main satellite performs several short (e.g., day-long)

excursions down to 120 km (perigee descents) using propulsion, measuring key electrodynamic properties through the heart 15

of the under-sampled region. At selected excursions, the main satellite releases the sub-satellites using the standardized

PPOD CubeSat release mechanism. The sub-satellites perform a multi-day to months-long orbit that gradually reduces its

perigee altitude due to atmospheric drag, eventually burning up in the mesosphere. During each sub-satellite release, co-

temporal measurements by the main satellite at higher altitude and the sub-satellite below offer unique and unprecedented

synchronized two-point measurements through the LTI region. This measurement scheme allows the investigation of cause-20

and-effect at different altitudes and offers the opportunity to measure, for the first time, the spatial extent and temporal

evolution of key under-sampled phenomena in the LTI. An example of the orbits of the main Daedalus satellite and a

deployed sub-satellite are shown in Fig. 1.

This paper describes the original Daedalus mission concept as proposed to ESA in response to a call for ideas for the 10th

Earth Explorer mission. The proposed concept has evolved from previous work carried out in the context of an ESA-GSTP 25

(General Support Technology Program) study that was performed as part of the Greek Task Force in 2009 (Sarris et al.,

2010), with a different set of constraints and accessible spacecraft and measurement technology. Upcoming Phase-0

activities have been put in place to review and consolidate concept, design and requirements within the new set of boundary

conditions associated with the Earth Explorer programme.

1.3 Measurement Gaps in the LTI 30

The lowest in-situ scientific measurements performed in this region by orbiting vehicles were made by the Atmosphere

Explorer (AE) series of satellites in the 1970’s. The perigee of these satellites extended as low as 140 km, but the dynamic


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range of some of the key measurements, such as mass spectrometer composition, made the data interpretation difficult at low

altitudes. Since then, in-situ measurements in the LTI have been limited to short crossings by sounding rockets, which by

nature give only a snapshot of the LTI over a single location, whereas, for example, to understand the spatial structure and

temporal evolution of key processes in response to a multi-hour solar storm, longer-term observations are required, across

different locations. Density measurements as low as 130 km have been inferred from the decay of low-altitude surveillance 5

satellites, and have been useful for understanding the gross features of the lower thermosphere, but the electrodynamics and

composition of the transition region between 100 and 200 km remain obscure. At higher altitudes, a series of spacecraft have

provided measurements of electric fields and density (CHAMP, DEMETER, GRACE, C/NOFS), but these are far from the

transition region, which remains under-sampled. Thus, information on this region arrives almost exclusively from remote

sensing, either from satellites (SME, UARS, CRISTA, SNOE, TIMED, ENVISAT, AIM) or from various ground 10

experiments (Lidars, Ionosondes, Incoherent Scatter Radars, Coherent Scatter Radars, Auroral Imagers, Photometers and

Fabry-Perot Interferometers). There is a wealth of information that these measurements are providing, and there are

significant advances in LTI science that have been accomplished, but there are also limitations that arise from the nature of

remote sensing techniques. For example, density and temperature measurements are unfortunately not possible or are largely

inaccurate in the 100-200 km region, as radiances become too weak and non-thermal above that altitude. Some major species 15

composition information is obtained by a combination of UV, IR and FPI measurements, but there is a significant gap in the

obtainable profiles at ~100-200 km due to lack of appropriate emissions for observation. It is also noted that different

observation methods may produce large deviations (even orders of magnitude) in estimates of key parameters in the LTI,

such as conductivity, ion drifts and neutral winds, with no baseline dataset for comparison.

2 Daedalus Science Objectives 20

The main scientific objectives are two-fold: On one hand, Daedalus will quantify, for the first time, the key unknown heating

processes in the LTI, and in particular the largely unknown Joule heating as well as energetic particle precipitation heating,

investigating how these affect the dynamics and thermal structure of the LTI, and how density, composition and temperature

of the LTI vary during periods of enhanced heating associated with extreme space weather events. On the other hand,

Daedalus will investigate the temperature and composition structure of the LTI in order to address a number of open 25

questions, such as: the processes that control momentum and energy transport and distribution in one of the most unknown

regions, the transition region at 100-200 km; the relative importance of the equatorial dynamo in driving the low latitude

ionosphere; the coupling of ions and neutrals in the low altitude ionosphere and thermosphere; the role of the LTI region as a

boundary condition to the exosphere above and stratosphere below; and the effects of the LTI region in the dynamics of the

exosphere and stratosphere. These are discussed in further detail below. 30


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2.1 Heating processes and Energy balance in the LTI

An overview of the energy and transport processes in the LTI resulting from the interaction with the near Earth space can be

seen in Fig. 2, showing the complexity of simultaneous processes such as: incoming energy from solar and magnetospheric

processes; lower atmosphere driving the low latitude ionosphere; Joule heating at higher latitudes; Energetic Particle

Precipitation (EPP) along field lines at high latitudes; the Auroral Electrojet - the large (~1 million Amperes) horizontal 5

currents that flow in the E-region (90-150 km) in the auroral ionosphere; and the Equatorial Electrojet - the large eastward

flow of electrical current in the ionosphere that occurs near noon within 5° of the magnetic equator. Radiative heating of the

LTI by extreme ultra-violet light (XUV) and x-rays from the Sun varies strongly with the 11-years solar cycle and is

responsible for the large temperature increase above the mesopause at about 100 km altitude. It's energy input is well

measured, however, after subtracting the solar cycle variations, a long term cooling is predicted through atmospheric general 10

circulation models (Rishbeth and Roble, 1992); this was found to be 10-15 K/decade through radar data over 33 years

(Ogawa et al., 2014). This is attributed to anthropogenic greenhouse cooling because of increasing absorption of infrared.

Joule heating, auroral particle precipitation and solar deposition of energy maximize in the altitude range 100-200 km. At the

same time, the composition between molecular and atomic species varies with the electrodynamic energy input and

atmospheric forcing, as well as with particle precipitation. These composition variations in turn modulate significantly the 15

efficiency of radiative heating, in both EUV and infrared. The 100-200 km region also involves large gradients and

variability in various parameters such as winds, temperature, density and composition; these parameters show different

behaviour between different latitudes. The processes that control momentum and energy transport are strongly tied to the

spatial and temporal variations of winds, temperature, density and composition; thus, whereas there is a fairly good physical

understanding of energy transport processes, there are few measurements of how the energy is redistributed, hindering the 20

exact quantification of these processes and their accurate modelling. Specifically, there is a lack of measurements of E-

region electric fields, ion drifts and ion composition and simultaneous measurements of neutral winds and neutral

composition.

Estimates of the range of energy input in the LTI by each of the main heating processes discussed above are presented in

Table 1. What is evident from this table is that the energy source with the largest variation, which can range from 25

comparatively insignificant levels to the single largest energy input, is Joule heating; second to that in both variation and

significance is Energetic Particle Precipitation. Particularly at high latitudes and at times of large solar and geomagnetic

activity, the Earth’s magnetic field couples the LTI to processes in the magnetosphere and the solar wind, which provide

heating that rivals or even exceeds the heating of the radiative component. The quantification and parameterization of these

processes is one of the primary science objectives of Daedalus. 30


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2.1.1 Joule Heating

Joule heating, or frictional heating, is caused by collisions between ions and neutrals in the presence of a relative drift

between the two (Vasyliūnas and Song, 2005). Ion-neutral friction tends to drive the neutral gas in a similar convection

pattern to that of the ions, which with time also generates kinetic energy (Codrescu, 1995; Richmond, 1995). Such drifts are

driven by processes in the magnetosphere and involve current systems between space and the ionosphere. These currents, 5

marked in Fig. 2 as field-aligned currents, were first envisaged by Birkeland more than 100 years ago (Birkeland, 1905):

they flow parallel to the magnetic field and they couple electrically the high-latitude ionosphere with near-Earth space. The

strength of these currents and their structure depend on solar and geomagnetic activity. In space they are well characterized

by a number of missions with multi-point measurement capabilities, such as ESA’s four-spacecraft Cluster mission (Amm,

2002; Dunlop et al., 2002) and the AMPERE mission, using magnetometer measurements from the Iridium satellites 10

(Anderson et al., 2000). However the closure of these current systems, which occurs within the LTI with a maximum current

density within the 100-200 km region, is not well sampled. This leads to large uncertainties in understanding and quantifying

Joule heating in this region. Joule heating is the most thermo-dynamically important process dissipating energy from the

magnetosphere, and it affects many thermospheric parameters, such as wind, temperature, composition and density, in a very

significant way; it is thought that its effects on the upper atmosphere are more significant than energetic and auroral particle 15

precipitation (e.g., Zhang et al., 2005), even though the exact ratio has not been successfully quantified to date. In a major

magnetic storm, Rosenqvist et al. (2006) estimated the power input into the magnetosphere to be ~17 GW by extrapolating

data from the Cluster mission; about 30% of this power could be dissipated as Joule heating in the ionosphere-thermosphere,

as inferred from EISCAT radar measurements and AMIE modelling. However, as discussed below, there are great

discrepancies in estimating Joule heating, depending on methodology and measurements used. 20

One of the big unknown parameters involved in Joule heating, and one of the issues that could be a source of the largest

discrepancies in its estimates, involves neutral winds, as Joule heating depends on the difference between ion and neutral

velocities in a complex way (Thayer & Semeter, 2004). For example, in the auroral oval the role of winds during active

conditions is to increase Joule heating in the morning sector, but to decrease it in the evening sector (Aikio et al., 2012; Cai

et al., 2013). Due to a lack of co-located and co-temporal measurements, neutral winds are usually neglected, and currently 25

height-integrated Joule heating is more commonly estimated in one of the following ways: (i) from the product of the electric

field and the height-integrated current density, E·J, (ii) from the product of the height-integrated Pedersen conductivity, ΣΡ,

and the square of the electric field, ΣΡ E2, where ΣΡ is estimated from models, or (iii) from the Poynting theorem, estimating

the field-aligned Poynting flux, in which the magnetic field is obtained through differences between measured and modelled

values. An overview of various methods to estimate height-integrated Joule heating is described in Olsson et al. (2004). 30

Traditionally, data sets that have been used for Joule heating estimates include measurements from ground radars (Ahn et al.,

1983; Aikio et al., 2012) and from low-altitude satellites, such as AE-C (Foster et al., 1983), DE-1 and DE-2 (Gary et al.,

1994) and Astrid-2/EMMA (Olson et al., 2004). Of these measurements DE-1 and DE-2 were the only spacecraft that


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performed simultaneous neutral wind and electric field measurements; however they only went down to 567.6 km and 309

km respectively, and, even though the region that the DE spacecraft sampled is certainly heated up after the deposition of

energy in the E-region, it is well above the region where Joule heating maximizes. Estimates have also been based on

empirical models such as the AMIE assimilative procedure (Chun et al., 1999), the GUMICS-4 MHD model (Palmroth et al.,

2004, 2005) and the CEJH empirical model (Zhang et al., 2005). 5

The uncertainty in obtaining accurate Joule heating estimates between the various methods is evident in Fig. 3, by Palmroth

et al. (2005), in which Joule heating is calculated through three different ways that are commonly used: on the top plot

measurements from the SuperDARN ionospheric radar network are used combined with Polar satellite measurements; on the

middle plot it is estimated through parameterizations that are used commonly, using empirical relationships with the AE and

Kp indexes as proxies; and on the lower plot by using the AMIE assimilation model from NCAR. What is particularly 10

striking in this plot is that there is up to a 500% difference among some of these estimates. Furthermore, it can be seen that

there is a significant difference on the timing (time scale is in hours) of when Joule heating starts: there is almost an hour

difference in the onset and peak of Joule heating. This is due to the lack of in-situ measurements where Joule heating occurs

and is an issue that is wide open to date. It is therefore of critical importance to fully understand the basic properties of Joule

heating and to fully quantify and parameterise its effects, in order to understand the processes in the high latitude ionosphere 15

and thermosphere. The correct quantification of Joule heating is also essential in order to properly and accurately include it

in models, thus being able to predict its relation to LTI dynamics and its contribution to the total energy balance. Some

questions related to Joule heating that remain open are: [1] What is the dependence of Joule heating on geomagnetic activity

and on energetic particle precipitation? [2] What is the relation of Joule heating to neutral wind, composition, temperature

and density? [3] What is the Joule heating distribution in space and time? [4] What is the time constant for momentum 20

transfer during Joule heating processes, and what is the dependence of this time constant on magnetospheric conditions and

thermosphere state? [5] What is the relation between Joule heating, upwelling and changes in neutral composition? [6] How

is Joule heating affecting and/or driving neutral winds at low latitude, what is its impact in redistributing heat, momentum

and composition, and how do these changes affect the lower atmosphere? and [7] How much Joule heating is involved in the

equatorial and mid-latitude tidal dynamos, in gravity waves and how does it affect the neutral atmosphere dynamics? 25

Since it is the coupling of ions and neutrals that determines Joule heating, in order to understand in-depth the Joule heating

process, and furthermore to perform Joule heating modelling accurately, simultaneous measurements of the ion drifts, neutral

winds, plasma and composition down to the E-region is crucial, together with measurements of the electric and magnetic

fields, as described in further detail in Section 3.3 below. These measurements have never been performed in-situ below 300

km, in the source region where Joule heating maximizes. There are radars that have made such co-located measurements 30

remotely, but these were localized and provided a weakly constrained estimate of what is happening at 300 km. Daedalus

employs a complete suite of measurements that will measure all the needed parameters to calculate Joule heating and the

thermosphere response and also differentiate under which conditions different approximations for Joule heating could be

valid. In order to quantify and understand the Joule heating process, local measurements at its source in the E-region where


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Joule heating maximizes are required. It is for this reason that the causal relationship of Joule heating to the thermosphere

dynamics remains to this date unresolved and that estimates vary so greatly.

2.1.2 Energetic Particle Precipitation

Energetic Particle Precipitation (EPP) is the second strongest energy source after Joule heating, both in terms of magnitude

and variation. Precipitating electrons, protons and Energetic Neutral Atoms (ENAs) deposit their energy into the atmosphere 5

at different altitudes, depending on particle energy. There are multiple effects caused by EPP: through the collisions with

neutral particles at high latitudes, precipitating particles ionize the neutral gas of the lower thermosphere and dissociate

atmospheric particles (Sinnhuber et al., 2012); they also heat up the lower thermosphere, produce bremsstrahlung X-rays and

auroras and increase the conductivity of the ionosphere. An estimate of the total ionization rate for EPP energies 1, 10 and

100 keV is given in Fig. 4. In particular, the increased ionization leads to increased conductivity that facilitates the flow of 10

current along the magnetic field lines and through the ionosphere, thus enhancing Joule heating. However, the direct

relationship between EPP and conductivity has not been established. It is therefore important to measure EPP, conductivity

and Joule heating at the same time. In addition, EPP (including energies much greater than 100 keV) significantly affects

atmospheric composition directly via the production of HOx and NOx, and indirectly through the descent of NOx to lower

altitudes (Codrescu et al., 1997; Randal et al., 2007). HOx and NOx, act as catalysts for ozone destruction in the mesosphere 15

(e.g., Seppälä et al., 2004), which, through a complicated radiative balance involving the amount of UV, can lead to impact

on terrestrial temperatures within the polar vortex (Seppälä et al., 2009). EPP and solar particle forcing on the mesospheric

chemistry can be so large that it can affect the atmosphere and climate system (Andersson et al., 2014), and therefore it has

received a growing attention also in the Intergovernmental Panel for Climate Change (IPCC) work. The largest issue in

relating the mesospheric ozone destruction with magnetospheric processes is that accurate estimations of particle energy 20

spectrum are lacking.

More energetic ions (E>30 MeV) and electrons (E>300 keV) penetrate down to the stratosphere, whereas the “medium”

energy ions (1<E<30 MeV) and electrons (30<E<300 keV) deposit their energy through ionization to the mesosphere and the

lower energy ions (E<1 MeV) and electrons (E<30 keV) to the thermosphere. ENAs, covering the energy range of ~1 keV to

~1 MeV, are produced via charge exchange when energetic ions interact with background neutral atoms such as Earth's 25

geocorona. Most of the energy density of ENAs is in the ~100 keV range. The energy transfer to the thermosphere due to

precipitating ENAs can be significant, particularly during heightened geomagnetic activity. Since they don't follow magnetic

field lines these particles play a role in mass and energy transfer to lower latitudes beyond the auroral zone. (Fok et al, 2003).

Measurements of EPP have been performed by multiple rockets as well as by various satellites; however, rocket

measurements are by nature short in duration, providing essentially only snapshots of vertical profiles, thus failing to capture 30

all phases of EPP and its effects on the LTI. EPP can also be estimated by inverting the electron density height profiles

measured by IS radars (e.g. Semeter and Kamalabadi, 2005). The inversion methods are based on ionization rate profiles like

those shown in Fig. 4, but the profiles depend on thermospheric density and temperature (Fang et al., 2010), which are taken


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from models. On the other hand, spacecraft such as POES, DMSP, SAMPEX, Polar and DEMETER have only performed

EPP measurements at higher altitudes, failing to measure in-situ the direct effects of EPP on lower thermospheric density,

temperature and composition. Several of these missions were also limited by having particle detectors with wide energy

channels (POES), whereas others could not resolve pitch angle distribution (DMSP). There is also considerable noise

between the electron and ion channels onboard POES SEM-2 instruments, making unambiguous measurements of EPP 5

difficult (Rodger et al., 2010).

In summary, it can be stated that Joule heating and EPP are critical parameters in understanding high-latitude and mid-

latitude processes in the LTI. Many aspects of the Joule heating process are not well characterized, and estimates of the

energy deposition vary greatly depending on the calculation method. EPP is a critical parameter of high-latitude energy

deposition that also affects Joule heating through altering conductivity. The combined measurements of neutral constituents 10

and energetic particles (ions, electrons and neutral atoms) is critical in estimating EPP energy deposition and for better

understanding of ionosphere-thermosphere coupling, and will allow scientists to resolve open questions about ion-neutral

interaction. Understanding both processes is imperative in understanding atmosphere as a whole.

2.1.3 Science questions related to Heating processes and Energy balance in the LTI

Related to the first science objective of Daedalus, key Science Questions that will be addressed by Daedalus are: 15

• What is the energy that is deposited into the LTI via Joule heating and particle precipitation and how does it affect

the dynamics and the thermal structure of the LTI (neutral density and wind, ion and neutral compositions, and

temperature)?

• What processes control momentum and energy transport and distribution in the transition region, at 100-200 km

altitude range in the high-latitude region? 20

2.2 Investigation of variations in the temperature and composition structure of the LTI

The second science objective of Daedalus involves the investigation of the temporal and spatial variability of key variables

in the LTI system. An overview of this variability can be seen in Fig. 5, showing the extreme values of neutral temperature

at different solar conditions (left), constituents of the thermosphere (centre) and constituents of the ionosphere (right) as a

function of altitude. These are further discussed in the following paragraphs. 25

2.2.1 Temperature structure of the LTI

In the left panel, it can be seen that the region from ~100-200 km is the transition region where the temperature increases

drastically from the mesopause to the thermosphere; higher up (particularly above 300 km) the thermosphere is essentially

isothermal. Temperature in the mesosphere (50-85 km) decreases with altitude, reaching a minimum at the mesopause;

above that, in the thermosphere temperature increases, and may range from 500 to 2000 K depending on solar and other 30

energy inputs, as well as on energy transport processes. The time-scales of temperature variations within this region also


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vary significantly from the lower-end to the upper-end of the transition region: whereas in the mesosphere temperature

measurements from ground-based lidars show a diurnal variation, remote sensing measurements of the region above 150 km

show a semi-diurnal variation. Many details of these time-scales are not well understood.

2.2.2 Composition structure of the LTI

A major characteristic of the neutral composition in the thermosphere is that, contrary to the mesosphere and stratosphere 5

below, its main chemical constituents, N2, O2, O, He and H tend to diffusively separate according to their individual scale

heights. In particular, the region from ~100 to 200 km, i.e. the region just above the turbopause, is believed to be the key area

where this transition takes place: Below a height of ~105 km, turbulence mixes the various species of gas that make up the

atmosphere and the relative abundances of species tend to be independent of altitude. This turbulent mixing process is

probably related to gravity wave breaking, but it is not known where and how the transition from turbulent mixing to 10

molecular diffusion occurs or how it varies globally, annually or on other time-scales. On the other hand, in the

thermosphere above ~200 km, composition is controlled by molecular diffusion; thus heavier species are concentrated lower

down, while the light ones dominate at the higher altitudes, so that, to first order, the density of each species decreases with

altitude at a rate that is related to its mass, according to nx(z) = n0e-z/H, where H = RT/mxg, mx is the mass of the species in

atomic units and R is the gas constant. Due to this diffusive separation, the main species N2, O2 and O show variations in 15

their densities that follow the lines of Fig. 5, as marked. From this figure, it can be seen that O becomes the dominant species

from about 200 km up to the top of the thermosphere. Below 200 km N2 is the most significant species, whereas below about

120 km O2 is more significant than O. The most abundant constituent from ~170-200 km and up to ~700 km is O, which

plays an important role in the energy balance in the lower thermosphere: O is responsible directly or indirectly for almost all

of the radiative cooling of the lower thermosphere by influencing the main radiative cooling terms, CO2 at 15 µm and NO at 20

5.3 µm (Gordiets et al., 1982), and thus it affects the response of the LTI to climate change. In particular, regarding NO,

despite the great amount of community effort in measurements and modeling, the temporal and spatial variability and

magnitude of the concentration of NO observed in the lower thermosphere remains largely unknown. Quantifying the

variability of O and O2 and the sources of this variability is a central challenge in upper atmosphere physics, and will assist

in obtaining a better theoretical understanding of upper atmosphere energetics and dynamics. 25

2.2.3 Science questions related to the temperature and composition structure of the LTI

In summary, temperature and composition structure in the lower thermosphere is extremely important for many processes

and remains under-sampled to a large degree, and many details of the time-scales of its variation in the LTI region are not

well understood. Related to the second science objective, key science questions that will be addressed by Daedalus are:

• What are the spatial and temporal variations in density, composition and temperature of the neutral atmosphere and 30

ionosphere at altitudes of 100-200 km altitude, with respect to solar activity?


11

• What is the relative importance of the equatorial and mid-latitude tidal dynamos in driving the low and mid latitude

ionosphere and how do ions and neutrals couple?

• What is the LTI region’s role as a boundary condition to the exosphere above and stratosphere below and how does

it affect their energetics and dynamics?

3 Daedalus Mission Requirements 5

3.1 Orbital Requirements

To resolve the above open questions, there is a need for measurements at different altitudes throughout the LTI and down to

extremely low altitudes where key electrodynamics processes such as Joule heating and EPP maximize, for an extended time

period. This is best realized by a spacecraft in a highly elliptical orbit, with a perigee that reaches as low as possible in the

100-200 km region; orbital simulations indicate that a nominal perigee of 150 km is feasible for a prolonged mission. In 10

order to perform measurements below the “observation barrier” of 150 km, the spacecraft performs several perigee descents

to lower altitudes, down to 120 km by use of propulsion. In order to perform measurements for a duration beyond one year,

an apogee higher than 2000 km is required, as discussed below. Most dynamic processes in the LTI, and in particular Joule

heating, maximize at high latitudes; thus a high inclination orbit is preferred. Finally, in order to investigate the cause-and-

effect of dynamic upper atmosphere processes, and to unambiguously differentiate between spatial and temporal effects, co-15

temporal measurements at different altitudes are required. This can be achieved by releasing from the main satellite

expendable sub-satellites that carry minimal instrumentation and which perform a spiralling orbit until they burn up in the

mesosphere. Such multi-point measurements offer the opportunity to measure, for the first time, the spatial extent and

temporal evolution of key under-sampled phenomena in the LTI.

3.2 Mission Duration 20

The LTI is highly variable, being influenced by variations in the solar, auroral, tidal and gravity wave forcing. These

variations occur over different time-scales: solar cycle (11-year), inter-annual (e.g., quasi-biennial), seasonal, and most

importantly diurnal. While multi-year missions to investigate solar cycle effects may be impractical in the LTI due to high

atmospheric drag, it is important to perform measurements in the thermosphere and ionosphere for as much of the diurnal

cycle, sampling the same latitude more than once during each season. A high inclination elliptical orbit, such as is required 25

to address key science objectives in the LTI, means that the orbit precesses in latitude over time. In order to provide

coverage of all latitudes, and also to sample the LTI region at different seasons, the minimum mission duration is one year,

and ideally three years, as a three year mission will significantly enhance measurement statistics of the response of the LTI

to solar events at different latitudes and will enhance the observational statistics of seasonal variations in key parameters and

processes. 30


12

The mission lifetime will depend on a number of parameters, such as apogee selection, spacecraft mass and cross-section,

spacecraft drag coefficient and the expected solar activity, which affects atmospheric density and the associated spacecraft

drag. In Fig. 6 we plot the expected Daedalus lifetime in days for different launch dates; the different curves correspond to

different spacecraft wet mass at launch (i.e., including propellant mass) and initial spacecraft apogee selection.

At the background of Fig. 6, the expected solar activity index F10.7 is calculated by Monte Carlo sampling of the six past 5

solar cycles. Lifetime simulations were performed using ESA’s DRAMA software, assuming a drag coefficient of 2.2

(suitable for a cylindrical satellite) and a total satellite drag area of 0.6 m2 (including the electric and magnetic field booms).

It is noted that increasing apogee altitude increases the mission lifetime, but leads to enhanced radiation exposure in the inner

radiation belt. This should be studied as part of a trade-off analysis, to be conducted during the initial Daedalus mission

phases. Finally, it is emphasized that the simulated lifetimes in Fig. 6 correspond to natural decay times, which can be 10

significantly enhanced with perigee/apogee maintenance by use of propulsion.

3.3 Measurement Requirements

In order to obtain accurate estimates of in-situ Joule heating, which is part of the Daedalus primary mission objective, a

number of parameters need to be measured. These are described below, through two commonly accepted expressions for

Joule heating estimates. The first one is: 15

𝑄! = 𝒋 · 𝑬 + 𝒖𝒏 ⨯ 𝑩 , (1)

where 𝒋 is the electric current density, 𝑬 and 𝑩 the electric and magnetic fields, respectively, and 𝒖! the neutral wind

velocity. 𝒋 can be inferred from magnetometer data, which is, however, not straightforward at altitudes where Pedersen, Hall

and Birkeland currents co-exist and all contribute to the local magnetic field, i.e. roughly below 300 km. Alternatively,

assuming quasi-neutrality, i.e. that the electron density 𝑁! is equal to the sum of the ion species densities 𝑁!!, 𝑁!!!, and 20

𝑁!"!, and denoting the electron and ion drifts for each species with 𝒗!, 𝒗!!, 𝒗!!!, and 𝒗!"!, respectively, we can replace 𝒋

in Eq. (1) as per Eq. (2):

𝑄! = e 𝑁!!𝒗!! + 𝑁!!!𝒗!!! + 𝑁!"!𝒗!"! − 𝑁!𝒗! ≈ 𝑒𝑁! 𝒗! − 𝒗! · 𝑬 + 𝒖! ⨯ 𝑩 , (2)

For the approximate equality we assume that all ion species drift with the same velocity 𝒗!. For strongly magnetized

electrons, which is a good assumption throughout the ionosphere down to below 100 km altitude, 𝒗! ≈ 𝑬 ⨯ 𝑩/|𝐵|! is 25

determined by measurement of 𝑬 and 𝑩. In-situ measurements of ion drifts, neutral winds, 𝑁!, and of 𝑬 and 𝑩 in an arbitrary

non-relativistic reference frame (for example the satellite’s reference frame) allow the estimate of the total local heating rate.

A different method to estimate Joule heating with in-situ measurements, involves Ohm’s law applied to ionospheric plasma

and estimates of the ion-neutral collision frequencies. Ohm’s law for the ionosphere with the electric field in the neutral

reference frame 𝑬∗ = 𝑬 + 𝒖! ⨯ 𝑩 is: 30


13

𝒋! = 𝝈!𝑬∗ − 𝝈!𝑬∗ ⨯ 𝑩/ 𝐵 , (3)

with 𝜎! and 𝜎! the Pedersen and Hall conductivities. Then Eq. (1), assuming no parallel electric field, 𝐸ǁ = 0, becomes

𝑄𝑱 = 𝝈! 𝑬∗ 𝟐 = 𝜎! 𝑬 + 𝒖! ⨯ 𝑩 !. (4)

In Eg. (4), the Pedersen conductivity, σP can be calculated as:

𝜎! =!!!𝑁!!

!!!!!!!!

! + 𝑁!!!!!!!

!!!!!!! + 𝑁!"!

!!"!!!!!!!

! + 𝑁!!!

!!!!! , (5) 5

In Eq. (5), ri represents the ratios of each species’ collision rate versus its gyrofrequency. The collision rates depend on a

number of terms, such as: on the density and composition of the ion and neutral species, which need to be measured

independently through mass spectrometry; on the ion and electron temperatures; and on the values for collision cross

sections. The latter are calculated primarily through laboratory experiments of ion-neutral collisions. However, these may

have systematic uncertainties in the upper atmosphere, and their accuracy has never been evaluated in-situ. These 10

measurements, through the comparison of the two methodologies described above, will also allow a new estimate of

collisional cross sections, which are needed and widely used in simulations, analysis of radar data etc.

Daedalus will have a complete suite of instruments to compare the two methodologies and to resolve which approximations

are valid. In summary, to evaluate all the parameters that go into Joule heating calculation in a local volume of space, the

required measurements are: neutral winds, ion drifts (along track and cross-track), ion density, ion composition and ion 15

temperature, electron temperature, neutral density, neutral composition (primarily N2, O, O2, N, NO) and neutral

temperature, magnetic field, DC electric fields and DC currents.

In Fig. 7 simulation results for Joule heating are plotted based on two physics-based models: TIE-GCM (left) vs. GUMICS

(right) for the same instance during the storm of April 6th, 2000, and with the same dynamic range for Joule heating (same

color-scale). A large discrepancy is seen between the two models, both in total amplitude but also in the spatial features. A 20

spacecraft that performs measurements of the actual parameters that go into Joule heating at various altitudes, and in

particular at the region where it maximizes, is the only way to provide an accurate reference for models and to identify

missing physics or inaccurately derived parameters.

As a preliminary step towards identifying the observation requirements of Daedalus, a number of upper atmosphere models

have been run and inter-compared in order to simulate the measurement performance requirements and dynamic ranges of 25

the proposed instruments. These models, together with the corresponding outputs that are related to Daedalus, are listed

below.

• TIE-GCM: Tn, Ti, Te, Zonal, Meridional and Vertical winds, O, O2, O+, O2+, NO+

• GUMICS-4: Magnetic Field, Electric Field, Pedersen and Hall conductivities, Energetic particle precipitation

Energy deposition, Joule heating, Field Aligned Currents 30

• IRI-07: Ne, Te, Ti, O+, O2+, NO+


14

• NRLMSISE-00: Tn, O, O2, Neutral density, Collision frequency

• FMI - Alpha parameter: Pedersen to Hall conductivity ratio

• HWM-07: Zonal neutral winds, Meridional neutral winds

As an example of the sampling of some of the above variables by Daedalus, the simulated storm-time zonal and meridional 5

winds are shown in Fig. 8; the simulated ground track of the orbit of a spacecraft that is sampling these winds is also plotted.

The dynamic ranges of these variables (i.e., the geophysical quantities to be observed by Daedalus) were estimated by

running the above models through extreme (minimum and maximum) geomagnetic activity conditions; in addition, the

sensitivity of the variables to model input parameters were investigated. An error analysis was conducted that modelled the

sensitivity of the resulting Joule heating to errors in obtaining each of these variables. A summary of the preliminary 10

estimates for the dynamic range in the region of interest and threshold accuracy and sensitivity of proposed key

instrumentation is listed in Table 2 below; these will need to be re-defined through a trade-off analysis as part of the initial

phases of the mission development, through an iterative process that involves science goals, instrument specifications,

spacecraft capabilities, and mission (orbit) analysis.

3.4 Instrumentation Requirements 15

The proposed suite of instruments to perform measurements of the parameters that go into Joule heating and particle

precipitation is listed in Table 2. The corresponding measured parameters, their dynamic ranges in the region of interest, and

the required threshold accuracy and sensitivity for each observable are also listed. Key scientific instrumentation that is

placed in the ram direction includes the IDM & RPA or TII, RWS & CWS and the IMS & NMS. The total surface area of

the ram direction instrumentation will determine the total cross-section of the spacecraft, which affects the mission lifetime; 20

hence care should be taken during the initial mission phases to minimize the total ram instrument surface. Three-axis

stabilization is required for instruments IDM & RPA or TII, RWS & CWS, IMS & NMS, with stringent attitude control and

pointing knowledge requirements.

4 Daedalus Mission Concept Overview

4.1 Orbital Design 25

Addressing the scientific objectives of Daedalus requires a spacecraft in a high-inclination (>85o) orbit that can perform

measurements at high latitudes within the altitude range of 100-200 km for a threshold duration of one year and a goal

duration of more than three years, in order to capture the response of the LTI region during all seasons and at all latitudes.

Preliminary orbital simulations indicate that this is feasible by a spacecraft with a perigee as low as 150 km and apogee

higher than 2000 km. By using an efficient propulsion system the total mission duration can be significantly increased (up to 30


15

several years). The need to minimize atmospheric drag is best realized by a torpedo-shaped spacecraft with a minimal cross-

section towards the ram direction and with body-mounted solar panels. The mission scenario includes the following parts,

shown in the schematic of Fig. 9:

• Part A: A satellite in a highly elliptical, dipping, high-inclination orbit with a perigee of 150 km and apogee

sufficiently high so as to maintain a mission lifetime above a threshold duration of one year and a goal duration of 5

three years performs in-situ measurements down to 150 km.

• Part B: The satellite periodically descends to 120 km altitude at selected passes using an efficient propulsion

system, performing measurements for a duration of one or more days and subsequently ascends to the nominal

perigee altitude of 150 km. At lowest perigee altitude the main satellite releases expendable sub-satellites.

• Part C: The sub-satellites are equipped with instrumentation such as a combination of accelerometers, 10

magnetometers and ion-neutral mass spectrometers, and complement the main satellite measurements at low

altitudes, providing critical 2-point estimates that enable the determination of the spatial extent and temporal

evolution of key electrodynamics processes below 120 km.

A simulation of the evolution of perigee and apogee for a sample mission scenario is shown in Fig. 10. This scenario

includes a perigee of 150 km, apogee of 3000 km, spacecraft dry mass of 300 kg, propellant mass of 100 kg, and 21 perigee 15

descents (“deep-dips”) from 150 km to 120 km. This simulation also includes perigee and apogee maintenance by use of

propulsion. With red are presented the osculating elements which include the short-term, the long-term and the secular

perturbations on the orbit, and with yellow are presented the Brouwer-Lyddane short mean elements i.e. averaging out the

short-term perturbations of the orbit according to the Brouwet-Lyddane theory (Brouwer, 1959 and Lyddane, 1963).

4.2 Instrumentation 20

In the following we provide details and requirements on the instruments that are proposed in order to address the scientific

objectives of Daedalus.

4.2.1 Ion Drift Meter (IDM) and Retarding Potential Analyzer (RPA), or Thermal Ion Imager (TII)

Ion drifts are needed to separate neutral wind dynamics from plasma motions in order to study Joule heating in the high

latitude LTI and to investigate the E-region and F-region dynamos at low latitudes. For Daedalus, the following options are 25

considered: An Ion Drift Meter (IDM) combined with a Retarding Potential Analyzer (RPA) or a Thermal Ion Imager (TII).

Description of the IDM: For the Ion Drift Meter (IDM), two sensors will be employed to directly derive the ion drift

velocity: a Retarding Potential Analyzer (RPA) to measure the plasma energy distribution along the sensor look direction,

and a planar Ion Drift Meter (IDM) to measure the arrival angle of the plasma with respect to the RPA sensor look direction.

The RPA will obtain ion temperature, drift velocity, and concentration by measuring incident variations in the ion flux. The 30

IDM will be used to obtain the arrival angle of the ions: in a common design, it is divided symmetrically into four equal pie

shaped segments, and it has a square aperture with sides parallel to the pie cuts. Therefore, any off-axis flow of ions results


16

in different currents in the four segments. This permits the transverse components of ion drift velocity to be measured. When

the other sensors face along the s/c velocity vector, the measured ion energy spectra can be used to deduce the component of

ion drift in that direction. Therefore, together with the RPAs the instrument is able to obtain the complete ion drift vector.

The IDM will also control the bias of a plate on the spacecraft's ram side, and will measure the plate current. For constant

bias the ion density can be estimated with high time resolution. A sweeping Langmuir mode will allow measurement of the 5

electron temperature as well. IDMs and RPAs have been widely used for studying ionospheric plasmas, obtaining

measurements from high altitude sounding rockets (Fang and Cheng, 2013), on the Atmosphere Explorers (AE) and the

Dynamics Explorers (DE) (Hanson et al., 1981), on the Communications/Navigation Outage Forecasting System (C/NOFS)

(Huba et al., 2014), and on Defense Meteorological Satellite Program (DMSP) satellites (Fang and Cheng, 2013).

Description of the TII: A Thermal Ion Imager (TII) has some heritage from an IDM/RPA, but also considerable differences 10

from the IDM/RPA concept, in that each of the two TII sensors use an electrostatic focusing system to produce two‐

dimensional (angle‐energy) images of low‐energy ion distribution functions; ions are directed to a micro-channel plate

(MCP), from where the signal is amplified and converted to an optical one with a phosphor screen. A CCD camera records

2D images of the ion distribution. Calculating the 1st and 2nd moments (partially on-board to reduce telemetry requirements)

gives the ion drift velocity vector and the ion temperature. For a full 3D distribution two TIIs oriented in orthogonal planes 15

are needed (with redundant measurements in the direction of the s/c velocity). All particles entering the instrument contribute

to observed images giving theoretically high sensitivity and good time resolution. TIIs are a relatively new development

(e.g., Knudsen et al., 2003) and have been flown on suborbital sounding rockets, on the Canadian ePOP satellite (a version

for electrons), and on the ESA Swarm satellites. On Swarm 1st moments of 2D images can be obtained at 16 Hz

corresponding to about 500 m spatial resolution. Full 3D ion velocity vectors and (potentially anisotropic) temperatures are 20

provided at 2 Hz (~3.5 km). As the s/c electric potential affects significantly the measurements, the Swarm TIIs are

complemented with Langmuir Probes, which also provide the plasma density eliminating the need for a highly accurate

calibration of the total TII particle fluxes. Some of the scientific results that have come from past TII measurements include

the characterization of mechanisms responsible for highly localized ion heating cavities (Burchill et al., 2004; Knudsen et al.,

2004), observations of ion upflow at speeds of hundreds of m/s within the polar cusp/cleft (Burchill et al., 2010), and 25

precision measurements of ion demagnetization versus altitude in the collisional lower ionosphere (Sangalli et al., 2009;

Burchill et al., 2012). Sangalli et al. (2009) compared TII‐measured ion drifts with double‐probe electric field and neutral

velocity measurements to establish a measurement accuracy of better than 20 m/s root‐mean‐square (RMS).

IDM/RPAs have often been used to also infer the electric field from the ion drifts, assuming that the ambient plasma is

strictly subject to an ExB drift; also on Swarm the EFI (electric field instrument) is actually a TII/LP ion drift combo without 30

any direct electric (E) field measurement. Similarly, if the electric fields are measured using a double-probe electric field

instrument, then the ion drifts can be calculated under the same assumption. However that is an assumption that cannot be

made safely much below 200 km, as at about 150 km the ion gyrofrequency drops below the ion collision frequency (see,


17

e.g., Kivelson and Russell 1995, Fig. 7.8). For this reason, both an electric field instrument and an ion drift meter are

required.

An IDM or TII for Daedalus will need to be able to handle a mixture of molecular ions (N2+, O2

+, NO+) and atomic oxygen

(O+), at least at lower altitudes below ~300 km. These are expected to have different ion drifts vi and, because of the mass

difference, of the composition of molecules and O+, and of the ion temperature Ti dependence, could not be derived 5

independently in RPA sweeps, or could be detected in a TII image at different locations for the same drift/temperature.

Instruments on previous missions sometimes separated O+ from H+ and He+, which is easier because of different masses by a

factor of >=4. The mass ratio of molecular ions and O+ is ≈<2. The transition between a plasma dominated by molecular ions

and one by O+ occurs between roughly 150 and 250 km altitude. Also Incoherent Scatter Radars (ISRs) have problems to

distinguish between molecular ions and O+ because of noise in the signals and also because of the relatively small mass 10

difference. A fallback solution is to use a relative composition from a model and fit Ti (ISR) or Ti and vi (in-situ ion

instrument). It should be noted, however, that models like the IRI-07 do not always give an accurate composition.

4.2.2 Ram Wind Sensor (RWS) and Cross-Track Wind Sensor (CWS)

Studies of the kinetics of neutral particle flow in the free molecular flow regime of the satellite environment led early on to

various concepts for neutral wind measurements. Based on these concepts, measurements have since resulted in a large body 15

of data of high spatial resolution. These data have revealed an unexpectedly complex and variable neutral atmosphere, a

signature of the deposition of large and highly variable quantities of energy. To resolve neutral winds two sensors will be

used on Daedalus: a Ram Wind Sensor (RWS) and a Cross-track Wind Sensor (CWS).

Description of the RWS: The Ram Wind Sensor (RWS) will obtain the neutral wind speed along the ram direction of

Daedalus by performing a retarding potential energy analysis on an ionized fraction of the flowing neutral gas. In such 20

configuration the incident ambient ions are electrostatically deflected from the instrument axis so that only the ions produced

from the flowing neutral beam have access to the electron multiplier detector.

Description of the CWS: The Cross-track Wind Sensor (CWS) will obtain the cross-track neutral wind velocity by

measuring small pressure differences created by the bulk motions of the thermal neutral gas in directions perpendicular to the

motion of the satellite. In the design employed by the CINDI instrument on-board C/NOFS (Earle et al., 2007, 2013), the 25

neutral wind instrument included four apertures on a hemispherical cover and operated by measuring the arrival angle of the

neutral wind at the satellite by detecting small pressure differences between neighbouring chambers with orifices pointing in

different directions (Hanson et al., 1992). The pressure measured in four cavities behind these apertures was related to the

arrival angle of the neutral gas relative to each aperture normal. Combined with detailed knowledge of the spacecraft

velocity vector, the pressure differentials between diametrically opposed cavities allowed the cross-track wind speed to be 30

determined in the satellite frame of reference. Ion gauges in each chamber measured currents proportional to the pressure and

ionization efficiency of any given neutral species (O'Hanlon, 1989). Both the CWS and the RWS will face in the ram

direction. It is noted that uncertainties in the wind velocity measurements can be introduced by small alignment errors during


18

instrument installation on the satellite, as through pointing errors in satellite attitude control or determination. A second

source of error can be introduced due to noise in the instrument electronics; these errors can influence both absolute and

relative measurements of velocities in the medium.

4.2.3 Accelerometer (ACC)

The accelerometer on-board Daedalus will measure non-gravitational accelerations such as air drag, Earth albedo and solar 5

radiation acting on the satellite. The direct measurement of acceleration α due to air drag can in turn be used to derive the

total atmospheric mass density ρ, through the fundamental relationship: α = ½ ρ V2 Cd A / m, where Cd, A, m, and V are the

s/c coefficient of drag, cross sectional area, mass, and velocity respectively (Hedin, 1991). Accelerometer data can also be

used to derive winds in the thermosphere (Sutton et al., 2007; Doornbos et al., 2010; Dhadly et al., 2018). Using expected

values of these parameters and obtaining values for ρ from the NRLMSISE-00 atmosphere model, it is calculated that the 10

drag acceleration will be on the order of 10-7g at 500 km and 10-3g at 120 km. This level of dynamic range is easily

accomplished with 16-bit analog-to-digital conversion. In order to obtain spatial resolution of ~1 km, a sampling frequency

of 16 Hz is required for a typical s/c velocity of ~8 km/s. Spatial resolution on the order of ~1 km is sufficient for resolving

Joule heating on a scale that can be compared to current models as well as for the detection of gravity waves in the lower

thermosphere. Sensitivity of ~10-7g will also allow the measurement of wind velocities around perigee. Acceptable 15

measurement errors are ±10% at 500 km and ±2% at altitudes below 200 km. In addition there may be a systematic error of

up to ±3% due to drag coefficient uncertainty. The accelerometer measurements will also monitor the thrust of the

propulsion system: a sensitivity on the order of ~10-4g to 10-3g is sufficient to accurately capture the orbit adjustments and

deep-dips of the spacecraft. A typical high-precision accelerometer configuration consists of three single-axis

accelerometers, mounted mutually at right angles and the instrument determines the applied acceleration from the 20

electrostatic force required to re-center a proof mass. The output is a digital pulse rate proportional to the applied

acceleration.

It is noted that the combination of an Accelerometer and reaction wheels of the Attitude and Orbit Control Subsystem

(AOCS) of the satellite will introduce restrictions on the usability of the accelerometer, at least for parts of the orbit. As part

of the early phases of Daedalus development, these will be further explored. Alternatively, it will also be investigated 25

whether the Mass Spectrometer of the satellite can be used to derive density with sufficient accuracy for the mission needs.

4.2.4 Energetic Particle Detector Suite (EPDS)

The Daedalus EPDS will consist of three distinct instruments: a High Energy Instrument (HEI), a Low Energy Instrument

(LEI) and an Energetic Neutral Atom (ENA) instrument. All three will be mounted to the spacecraft with a clear upward-

looking Field-of-View (FoV) that will allow full pitch angle (pa) coverage of precipitating particles. 30

HEI will provide high-resolution differential energy measurements of relativistic electrons and protons/heavy ions

precipitating into the LTI environment, with pitch angle resolution capable of resolving the distributions of EPP flux within


19

the bounce-loss-cone. Electron measurements will be performed in an energy range spanning <40 keV to >1 MeV and

protons/heavy ion measurements from <1 MeV to >10’s MeV. HEI will be based on a solid-state detector, combining recent

advancements in solid-state detector design. The design will need to include detailed modelling of energetic particle-matter

interactions such as GEANT4 simulations, to employ Digital Signal Processing (DSP), and to be able to support advanced

real-time characterization algorithms and counting rates up to 106 counts/sec. A primary benefit of utilizing DSP is pile up 5

detection and recovery, making dead time essentially negligible after correction.

LEI will consist of an electron sensor and a proton sensor: The LEI electron sensor will provide the 3D velocity distribution

(fluxes vs. energy and pitch angle) of thermal and supra-thermal electrons in an energy range spanning <30 eV to >30 keV.

The LEI proton sensor will provide energy coverage between >1 MeV, which is the proton threshold of HEI, and the few eV

or 10s eV ions measured by the IMS (see following section). It is noted here that precipitating ions of a few 10s keV can lead 10

to significant enhancements of electron density and conductivities (e.g., Yuan et al., 2014). Heritage electron sensors have

already performed measurements at the altitudes of Daedalus on a number of rocket flights, and have returned excellent

science data. Heritage sensors commonly utilize an electrostatic analyser to provide measurements of precipitating electrons

at high cadence with high energy and pitch angle resolution, enabling quantification of the energy input into the

thermosphere and ionosphere. Electrostatic analysers are well understood and have high heritage (Doss et al., 2014), dating 15

back to the original Carlson et al. (1983) top-hat design. Electrostatic analysers bias the inner of two concentric hemispheres

to a positive voltage to select electrons by energy, with high energy and angular resolution ensured by the natural focal

properties of the electrostatic analyser. Electrostatic analysers count individual particles, typically utilizing micro-channel

plate (MCP) detectors with a segmented anode to collect charge pulses, and charge-sensitive amplifiers to convert pulses into

digital counts. For Daedalus, electrostatic deflectors will be required to increase the FoV to cover at least ~70% of the 20

distribution (Sauvaud et al., 2008), including upward-going and downward-going electrons. Upward-going electrons provide

information about magnetic and electric fields below the spacecraft, and are therefore a secondary science topic.

Measurements will need to be made fast enough to resolve spatial structures ~100 km, requiring 10 s or better cadence. To

cover typical supra-thermal electron precipitating fluxes, the sensor will need to be capable of measuring differential energy

fluxes of 106-5x109 eV/[cm2 s sr eV] with good statistics in this 10s interval, without saturating. 25

ENA instrument will measure neutral atoms in the range from ~5keV to ~200keV, which covers the typical range of

significant energy density in ENAs generated by charge exchange in the ring current. In common designs, instruments use a

thin-window, low-threshold, pixelated solid-state detector (SSD) to measure precipitating ENAs, and the SSD is read out

with a low-resource ASIC. Counts can be flexibly accumulated on an instrument FPGA to match the science requirements.

Electrostatic deflection will need to be used to sweep low energy charged particles out of the instrument field of view. The 30

pixelated SSD will allow for coarse imaging of the ENA flux as well as refined separation of ENAs from energetic charged

particles.


20

4.2.5 Ion Mass Spectrometer (IMS) and Neutral Mass Spectrometer (NMS)

The IMS and NMS instruments will measure the composition and density of the main ion and neutral species along the

spacecraft orbit; more specifically of ion species H+, He+, N+, O+, NO+, O2+ and of neutral species H, He, N, O, N2, NO, O2

(and desirably CO2) in the altitude range ~100 km to >500km. The threshold mass resolution M/dM is ~30, driven by the

requirement to separate between NO and O2. The target mass range is driven by the heaviest species; a mass range of ~>40 is 5

adequate to resolve up to Argon with margin. It is noted here that the spacecraft propellant will need to be selected so as not

to interfere with NMS measurements. Regarding the dynamic ranges, as it can be seen from Fig. 5 the altitude ranges from

100 to 500 km correspond to density variations from ~102 to 106 /cm3 for the ions and from ~104 to 1014 /cm3 for the neutrals

and to temperature variations from 200 to 2000 K. Furthermore cross-track and along-track ion drift and neutral wind

velocities can vary in the range of ± -4 km/sec and ± 1 km/sec respectively. Because of the relatively cold temperatures the 10

thermal velocities √(KT/min) of the various particle species (e.g. 1.8-5.7 km/sec for H, 0.9-2.86 km/sec for O, 0.64-2 km/sec

for O2) are significantly smaller than the spacecraft velocity of ~8 km/sec and on the same order of magnitude as the ion drift

and neutral wind speeds. As a result the various ion and neutral particle velocity distributions will appear like beams (i.e.,

wider for high temperature light species and narrower for low temperature heavy species) on the spacecraft frame of

reference. The bulk peak energies vary proportionally to V2 with V in the range 4-12 km/sec for ions and 7-9 km/sec for 15

neutrals (0.08-0.75 eV for H+, 0.26-0.42 eV for H, 2.5-24 eV for O2+, 8.3-13.5 eV for O2); the bulk beam angle with respect

to the spacecraft ram vector vary in the range ±26.5o for ions and ±7.1o for neutrals. To adequately capture the distributions

the IMS and INS should be designed with a FoV of ±75o for ions and ±21o for the neutrals and for energy range up to 0-35

eV. Therefore the particle flux measurements of each species on the spacecraft frame of reference as a function of the look

direction in polar coordinates (θ, ϕ), can be written as Rsc_in(θ, ϕ) = F(A, Nin, Tin, Ein, Vin,Vsc, Altsc), where A is the instrument 20

aperture area, Nin, Tin, Ein are the density, temperature and energy for each ion/neutral species, and Vin, Vsc, Altsc are the

vectors for the ion drift / neutral wind velocities, the spacecraft velocity and spacecraft attitude. Because of the frequent

collisions at low altitudes the particle distributions for each species can be well approximated as Maxwellian distributions (in

the general case with kappa distributions) drifted at the vector sum velocity of Vin + Vsc. With a multi – parameter fit of the

flux measurements Rsc_in(θ, ϕ) and minimizing the least mean square error one can get the total solution for the density of the 25

various ion and neutral densities Nin, temperatures, and of the ion drifts and neutral winds. Because of redundancy, the

proposed IMS/INS suit will emphasize in the mass analysis and sampling of the relative densities of each species, taking

inputs the ion/neutral temperatures and drift/wind vector measurements from the dedicated IDM/RPA and CWS/RWS

instruments.

The proposed mass spectrometer method is based on electronically gated Time of Flight (ToF), in which an acceleration 30

voltage of few hundred volts energizes up all particles to about the same energy and orders the velocity of all the ions

according to the square root of their mass. An electric gate controls the flow of particles from the gate to the detector. The

mass of the particles is determined from the ToF measurement at the particle energy. Unlike usual plasma mass analysers


21

based on foils, the gated ToF method is non-destructive and therefore well suited for molecular species. Contrary to other

methods that scan the mass spectrum (quadrupole mass spectrometers), the ToF method measures all particles

simultaneously, a key capability for fast sampling in the transition regions. Also most importantly the electronic gating

allows controlling the geometric factor and boosting the detector bandwidth by several orders of magnitude beyond the

continuous detector capability of ~107 cps. This feature enables handling the neutral density dynamic range of ~1010 and the 5

sampling requirement of >=16 samples per second. Heritage of gated ToF IMS and NMS include instruments flown onboard

the Exocube mission (launched in January 2015 in high inclination LEO orbit) and the Dellingr mission deployed in

November 2017 from the ISS (Paschalidis et al., 2016; Paschalidis et al., 2019).

In a common design, the core sensor consists of a top-hat electrostatic analyser, surrounded outwards by a circular gate, by

an RPA, by a collimator and by deflectors; thus the sensor can intrinsically cover the entire 4pi sky with the deflector 10

scanning. However for the main satellite the FoV will be limited to +/-90o azimuth and +/-75o elevation scanning and the

IMS will be performing mass analysis for each look direction. Although the angular imaging will be redundant to the IDM, it

can be useful in areas of low densities where IDMs are limited in sensitivity. In addition, although the RPA feature of the

IMS will be redundant to the dedicated RPA instrument, the IMS/RPA can be used to block low energies and to do mass

analysis on the non-thermal tail of the ion distributions. Without the elevation and RPA scanning the IMS performs mass 15

analysis in each azimuth direction. Thus the IMS will do faster relative density sampling of each species and the dedicated

IDM/RPA instruments could be used for calibrating for total density, temperature and in-track and cross-track ion drifts.

It should also be noted that the best orientation of the IMS and NMS instruments will be with the long FoV (azimuth) on the

horizontal plane and perpendicular to the ram direction, in order to match the larger horizontal ion drift and neutral winds

compared to vertical. This orientation will reduce or eliminate the vertical scanning (elevation) and thus simplify the 20

instrument design.

4.2.6 Electric Field Instrument (EFI)

The Daedalus Electric Field Instrument (EFI) will be designed to make high-accuracy measurements of in-situ electric fields,

spacecraft surface potential and plasma density. The arrangement of six spherical probes mounted near the tips of six

deployable stacer booms will enable 3D in-situ measurements using the well-established double probe technique (e.g. 25

Mozer, 2016). Boom orientation will be such as to minimize interference due to the spacecraft plasma wake (e.g. Cully et al.,

2007), as in Fig. 11, and to minimize optical shadowing of probe surfaces by the spacecraft body and its protrusions. Each

probe will also measure electric potential relative to the s/c. The probes will be current-biased to ensure steady plasma

sheath resistance, and therefore steady instrument gain at low frequencies (Bale et al., 2008). In the Daedalus plasma

environment (120 km to 500 km), rigid booms of lengths > ~4m place the probes many Debye lengths from the s/c, 30

minimizing errors due to s/c surface potential inhomogeneity. A voltage-biased ‘stub’ element will mechanically support

each probe and provide electrical isolation from the booms. Each probe will contain a low-noise, high impedance

preamplifier, able to pass signals to the s/c. With 8.2 m probe separation, electric fields up to ~3.6 V/m can be measured.


22

This range is sufficient to measure geophysical electric field variations on top of the electric field induced by spacecraft

motion (up to ~450 mV/m near perigee). The high oxygen density in Daedalus' orbital environment, in particular near

perigee, will cause EFI probe surfaces to oxidize. Oxidation of probe surfaces can create an electrically resistive layer on the

probe surface (Ergun et al. 2015), or it can erode probe coatings entirely (Vistine 1983, Vistine et al. 1985). Either effect can

degrade or destroy the ability of EFI to measure DC-coupled electric fields (Mozer et al. 2016). EFI probes coatings will 5

need to be selected so as to mitigate the effects of oxidation to maintain instrument performance. In the double-probe

technique, signals from the probes are passed to the EFI electronics box (EB), where they undergo analog processing,

including amplification and filtering. The EB will also contain components for driving probe and stub biases and possibly

electronics to support a relaxation sounder. All science signals will be digitized by analog-to-digital converters (ADCs) and

will undergo digital processing. Digital algorithms will produce time-series waveform and spectral data products with a 10

wide range of selectable cadences. The EFI may also include a relaxation sounder to measure the local plasma density with

high accuracy (Trotignon et al. 2003, Andersson et al. 2015). Alternatively a Mutual Impedance Probe (MIP) or a Langmuir

Probe (LP) will be considered, both of which are capable of measuring the local plasma density as well as temperature.

The EFI design as proposed to ESA has the following heritage: Preamplifier designs for EFI instruments have strong

heritage. The proposed stacer booms have direct heritage from the French DEMETER mission (Parrot et al. 2002). The 15

preamplifier design has strong heritage from MMS/FIELDS/ADP (Ergun et al. 2016), while the EFI signal-processing

heritage includes THEMIS/EFI (Cully et al., 2008), Van Allen Probes/EFW (Wygant et al., 2013), MAVEN/LPW

(Andersson et al., 2015), MMS/FIELDS (Ergun et al., 2016), and Parker Solar Probe/FIELDS (Malaspina et al., 2016). The

relaxation sounder has direct heritage to MAVEN/LPW (Andersson et al., 2015), whereas the MIP would inherit from the

Rosetta/RPC (Trotignon et al, 2007). In each case antenna geometry and frequency range should be adapted appropriately 20

for the Earth’s ionosphere. Other heritage electric field instruments include those flown onto ISEE3 (Scarf et al., 1978), and

Cluster. In each case antenna geometry and frequency range will be adapted appropriately for the Earth’s ionosphere.

4.2.7 Magnetometer (MAG)

High-precision measurements of in-situ magnetic fields are crucial for Joule heating estimates, for deriving current structures

in the ionosphere and for studying and interpreting EPP fluxes and magnetosphere-ionosphere current systems. The 25

Daedalus magnetometers will measure both DC and AC magnetic fields: DC magnetic field measurements are a required

measurement in Eq. (1) and (4) of Joule heating and Eq. (5) of Pedersen conductivity; they are also needed for determining

the pitch angles of precipitating charged particles, as measured by the EPDS. DC magnetic field measurements also allow for

a quantitative determination of the upward and downward currents traversed by the instrument: there are well-established

methods for extracting current measurements from in situ magnetometer data (Ganushkina et al., 2015; Ritter, et al., 2013), 30

but they all rely on a priori assumptions about the structure of the currents. This is because single point magnetometer

measurements do not uniquely determine a current structure, as there are typically many current structures that can produce a

given magnetometer signature. For this reason it is useful to simultaneously measure particles (electrons and ions), which


23

provide much-needed constraints on the current estimates. In addition, more accurate determination of the current structures

will be enabled during the times of the sub-satellite releases via multi-point measurements. The AC magnetometer

measurements are useful for measuring wave phenomena, as electromagnetic waves (such as Alfvén waves) have magnetic

signatures that can be detected.

Heritage high-precision magnetometers include, e.g., the vector field magnetometer developed by DTU Space, National 5

Space Institute of Denmark, a fluxgate magnetometer developed by the Institut für Geophysik und extraterrestrische Physik

of the Technische Universität Braunschweig (Auster et al., 2007, 2008, 2010), a scalar magnetometer developed by the

Space Research Institute of the Austrian Academy of Sciences and the Institute of Experimental Physics of the Graz

University of Technology, an absolute scalar magnetometers developed by the National Centre for Space Studies and French

Atomic Energy and Alternative Energies Commission/Electronics and Information Technology Laboratory (Léger et al. 10

2015; Fratter et al., 2016). All these magnetometers have been used or are currently deployed in different satellite missions

and will ensure the 50 Hz or higher measurement frequency of the magnetic field with the accuracy and cleanness less than 2

nT and 0.1 nT respectively. To achieve these parameters the magnetometers have to be deployed on a boom, such as shown

in the aft of the spacecraft in Fig. 16, with a length between 0.5 and 2 m; simulations are necessary to determine the exact

length, through a trade off between the stability of the satellite and the accuracy of the measurements. In order to perform 15

multipoint magnetic field measurements that will significantly increase the scientific gain, it is recommended to have at least

a scalar magnetometer on the sub-satellites.

4.2.8 Global Navigation Satellite System Receiver (GNSS)

Global Navigation Satellite System (GNSS) receivers are commonly used for ionospheric tomography and for Total Electron

Content (TEC) measurements. The underlying principle in this technique is that the ionosphere, being a weakly ionized 20

plasma or gas, affects the propagation of GNSS radio signals. In order to quantify the propagation effects on a radio wave

travelling through the ionosphere the refractive index of the ionosphere must be specified (Yizengaw and Essex, 1999). The

refractive index of the ionosphere, n, is given by the Appleton and Hartree equation as: n = 1 – X/2 = 1 – 40.3 N / f 2, where

N is the electron density. This expression has been proven to be accurate to better than 1%. Subsequently, knowing the

refractive index of the ionosphere, it is possible to derive the total number of electrons in the ionosphere, the parameter of 25

the ionosphere that produces most of the changes on the GNSS signal along the GNSS signal trajectory from each satellite to

the observer. TEC is expressed as the number of electrons in a vertical column having a one square meter cross section, and

extending all the way from the GNSS satellite to the receiver. Regarding GNSS-derived TEC products, Daedalus will build

on the heritage from CHAMP, GRACE and COSMIC. The GNSS receiver will also be used for attitude knowledge.

4.2.9 Sub-satellite Instrumentation 30

The proposed Daedalus mission concept includes expendable small sub-satellites in the form of CubeSats that are released

from the main satellite. The sub-satellites are released during the main satellite’s perigee descent to lower altitudes and, after


24

the main satellite ascends to higher perigee, the sub-satellite measurements at lower altitudes provide estimates of the

vertical gradients and the temporal evolution of key LTI parameters. Different instrument combinations will be investigated.

Potential instrumentation and their measurement objectives are discussed below; these will be further investigated during the

initial phases of the Daedalus mission defintion: (a) Accelerometer and Laser retroreflectors (a light-weight, passive

instrument designed to reflect laser pulses back to their point of origin on Earth) can be employed to determine atmospheric 5

density. This will allow resolving the time constant for density increases at lower altitudes after a solar storm and the vertical

extent of the density changes due to Joule heating. The sub-satellites that carry accelerometers will need to be 3-axis

stabilized. (b) Miniaturized INMS can provide composition measurements of the primary constituents at lower altitudes; this

will allow resolving the altitude profile of key constituents, while being able to cross-calibrate the INMS on the main

satellite and the sub-satellite. In addition, ion and neutral composition will enable estimates of Pedersen conductivity, σP at a 10

second point along a field line below the main spacecraft, something never available before via in-situ measurements. (c)

Miniaturized Energetic Particle instruments, to determine EPP at lower altitudes and provide the altitude distribution of

particle precipitation. (d) There have been recent efforts to combine the IDM and RPA instrument functionality into one

lightweight, small, low-power unit ideal for small satellites, including CubeSats (Hatch, 2016; Swenson, 2017); testing has

shown that the design, while saving on power and space, does not compromise much in terms of instrument accuracy relative 15

to using two separate instruments. The combination of an RPA/IDM on the main satellite and on a second point down below

would allow the determination of the altitude distribution of ion drifts. Another example includes the Advanced Ionospheric

Probe (AIP), with flight heritage onboard FORMOSAT-5 satellite (Lin et al., 2017); the AIP is an all-in-one plasma sensor

that measures ionospheric plasma concentrations, velocities, and temperatures. (f) Magnetometer measurements at a second

point below the main Daedalus spacecraft, and at the same orbital plane, will enable observations of currents along similar 20

field lines (with some phase difference, due to the slightly different orbital periods), allowing speculations about the current

density gradients as a function of altitude, something that has not been possible before. (g) Finally, the sub-satellites can

carry a radio occultation measurement device, sending signals to the mothership. The signals from the radio occultation

device will be used to determine the density in the vicinity of the mothership, which makes an in situ measurement.

Together, these signals can be used to make a 3D tomography of the density structure for the first time. 25

4.3 Further Observational and Measurement Requirements Relevant to the Mission Concept

In the following, we provide further details of observational and measurement requirements placed on the Daedalus mission

concept in terms of the observation geometry and placement of the instruments, the observing scheme of the main satellite

combined with the sub-satellites, spatial and temporal coverage and resolution, and a preliminary assessment of accuracy

requirements; these will be further consolidated during the first phases of the Daedalus mission definition. 30


25

4.3.1 Observation Geometry

The following key scientific instrumentation needs to be placed in the Daedalus spacecraft ram direction: IDM-RPA (or TII),

IMS-NMS, RWS-CTS. Three-axis stabilization is required with stringent attitude control and pointing knowledge

requirements. The need to perform in-situ measurements in the Lower Thermosphere - Ionosphere is best realized by a

spacecraft with minimal cross-section and with body-mounted solar panels to minimize drag effects. A preliminary design of 5

Daedalus with extended electric field booms and an overview of the instrumentation that needs to be placed in the ram

direction of the spacecraft, thus defining the minimum cross-section, are shown in Fig. 11.

4.3.2 Observing Scheme

Daedalus will perform the episodic descents to lower altitudes during times of varying solar wind conditions to parameterize

the response of the LTI to external driving. Initially the episodic descents will be planned during quiet times, when 10

thermosphere density and satellite drag are lower; subsequent descents will be performed during active times, planned based

on space weather predictions. Descents can be performed in a step-wise manner, in order to perform measurements at

different perigee altitudes, and also to ensure safe descents and to avoid excessive loss of spacecraft velocity due to

unexpectedly high satellite drag. An overview of the observing scheme through the complex high-latitude current system is

given in Fig. 12. The orbits of the main (green) and a sub-satellite (red) are shown both for the mission phase when perigee 15

is at high latitudes (solid lines), when the satellite can perform in-situ measurements in the region where Joule heating

maximizes, and also at times when apogee is at high latitudes – due to precession of the orbit’s semi-major axis (dashed

lines), when vertical gradients of Field-aligned currents and EPP can be investigated. Schematic locations of the Pedersen,

Hall and Field-aligned currents are also drawn. Several mission scenarios can be executed: If a sub-satellite is released in

association with a solar storm then one can look at the time history during and after the storm; by quantifying Joule heating 20

in-situ and by monitoring the density enhancements and composition changes at various altitudes below, Daedalus will allow

estimates of the extent and distribution of the Joule heating region and enable calculation of the total energy deposition

during the storm. When the perigee is at low-latitudes, dynamo mechanisms can be studied with two-point observations,

ideally with one point in the E-region and one point in the F-region, such that the actual creation of the dynamo can be

observed at low altitudes and the effects of the dynamo mechanism can be observed at high altitudes. Daedalus can also test 25

theoretical explanations for the equatorial anomaly (Appleton, 1946), which has not been measured in-situ before with multi-

point measurements.

4.3.3 Spatial Coverage and Spatial Resolution

The region of interest for the primary science objectives is from 100 to 200 km, however measurements will be performed

from altitudes of 500 km and downwards in order to provide context measurements and to cover the entire range where Joule 30

heating and other energy transport processes take place. The upper limit of 500 km is set due to limitations in the maximum


26

dynamic range that the IMS and NMS can achieve, but can be extended upwards on a per instrument basis in order to allow

conjunctions with other missions at higher circular orbits and/or the investigation of phenomena that extent to higher

altitudes. Instruments such as EFI, MAG and EPDS can operate along the entire orbit, to allow additional science objectives

to be addressed. An example of the relation between spatial resolution and temporal resolution is given in Fig. 13, obtained

through sampling the NRLMSISE-00 model along the simulated orbit. 5

It should be noted that vertical resolution is a very important parameter, more critical than horizontal resolution, as, to first

order, the vertical profile determines to a larger degree how energy is distributed, rather than the longitudinal profile. A

secondary consideration is the latitudinal structure of the observed features. An initial vertical resolution of 0.5 km for the in-

situ sampling of key LTI parameters is baselined, with a higher threshold resolution of 0.25 km at altitudes below 150 km,

during the perigee descents. Regarding the latitude-longitude coverage, it is preferable to keep perigee at as high a latitude as 10

possible, which is a trade-off in the ellipticity of the orbit: the more elliptical the orbit, the less the perigee precesses.

However the more elliptical the orbit, the longer the orbital period becomes and thus the revisit time at perigee suffers.

Finally, perigee precession allows measurements at both at high and low latitudes to be performed, thus allowing

measurements of Joule heating and EPP at high latitudes and also the equatorial electrojets. These will be determined

through a trade-off analysis; an example of the long term evolution of Daedalus argument of perigee, inclination, right 15

ascension of the ascending node and eccentricity for the sample orbit of Fig. 10 are shown below in Fig. 14.

4.3.4 Temporal Coverage and Temporal Resolution

The temporal coverage needs to be reconcilable with the spatial and temporal scales of the phenomena under investigation.

In general, the thermosphere and ionosphere have a response and relaxation time on the order of days. At low latitudes the

dynamics are a diurnal phenomenon, but one that can change every day. The measurement strategy of Daedalus will be to 20

measure all local times with a precessing satellite. At mid- and high-latitudes dynamic timescales are on the order of hours:

for example, Joule heating happens over the course of several hours. During a large storm, the dynamic timescale is days.

This, in turn, defines the timescale required for the repeat cycle. In the mission concept described herein, the main spacecraft

has an orbital period of ~120 min and will provide the required temporal coverage to identify diurnal variations and the

response and relaxation of the LTI to external solar driving. At the same time, the combination of the main spacecraft with 25

sub-satellites will provide measurements to separate temporal from spatial effects and will also enhance the repeat cycle of

the main satellite with context measurements. Regarding temporal resolution, all instrument signals will be recorded below

500 km at ≥16 sample/s, giving a horizontal resolution ≤1 km. Brief segments will be recorded for later playback as ‘burst’

data, especially during the deep-dips of the spacecraft, or other selected time intervals.

It is noted that the sub-satellites will be released at a lower perigee and they will have a different cross-section-over-mass 30

ratio than the main satellite as well as different drag coefficients; thus they will be flying at slightly different velocities than

the main satellite. This means that measurements at two different altitudes over the same latitude-longitude will have a

temporal offset that will increase as the satellites drift apart, as shown in the orbital simulations of Fig. 15. The maximum


27

temporal offset for the co-registration of measurements by the main satellite and the sub-satellite will be equal to half the

orbital period, or ~60 minutes. However the time-scales of events under investigation are on the order of several hours to

days; thus the maximum temporal offset between the measurements at the two altitudes is acceptable and provides important

information for the spatial/altitude scale of events in the LTI.

4.3.5 Measurement Accuracy Requirements 5

To address the primary science objectives of Daedalus, and in particular the determination of Joule heating, precise vector

neutral wind and ion drift measurements are required. The most stringent stability and alignment requirements are dictated

by the IDM and the neutral wind sensors (RWS and CTS). The IDM needs to be pointing constantly towards the direction of

travel of the spacecraft (ram direction). Thus 3-axis stabilization is required. 3-axis stabilization is also ideal for particle

measurements. Thus the spacecraft should be aligned so that the first axis always points towards the ram direction 10

(horizontal axis), the second axis points towards the center of the earth (vertical axis) and the third axis completes the

orthogonal system (horizontal axis). Instruments for ion drift and neutral wind determination have commonly a FoV of ±45o;

this could be aligned in the ram direction, since generally pointing is known better in that direction. A trade-off analysis

should be conducted to identify the optimal means to achieve the required alignment; it is noted here that reaction wheels

will potentially hinder accelerometer measurements, which are needed for density determination. Errors in pointing 15

knowledge will propagate onto errors in ion and wind speeds; for the Daedalus spacecraft orbit at perigee, 1 degree of error

in pointing knowledge corresponds to 140 m/s error in knowledge of ion drifts and winds. Observation requirements for

Joule heating determination lead to an estimated required spacecraft pointing knowledge to within 0.02o accuracy in the

vertical direction (< 3 m/s accuracy in ion drift & wind speed) and 0.14o accuracy in the horizontal directions (< 20 m/s

accuracy in ion drift & wind speed); these will be consolidated during the initial phases of the Daedalus mission definition. 20

To achieve the above pointing knowledge and alignment, 2 star cameras are baselined.

4.4 Spacecraft Design Constraints and Design Considerations

The low altitudes that Daedalus targets pose a number of technical challenges. To overcome these challenges, the original

design of Daedalus was based on the following criteria, and an initial layout with subsystems as shown in Fig. 16:

4.4.1 Spacecraft Structure 25

The structure of the main Daedalus spacecraft should employ an aerodynamic design to compensate for increased drag

during perigee passes at low altitudes. The minimum cross-section is determined by the ram direction instrumentation and by

the cross-section of the deployed electric field booms. The former should be minimized in collaboration with instrument

designers and the latter should be designed as narrow as possible while maintaining stability and rigidity in the high-drag

environment during perigee. The preliminary design has a cross-sectional area of 0.4 m2 for the spacecraft body and a cross 30

section of 0.2 m2 for the stacer booms; if these could be significantly reduced, further increases in the mission lifetime could


28

be realized. The use of special fins or structures should be investigated as part of the Daedalus feasibility studies, to increase

the aerodynamic stability while minimizing the drag coefficient (Cd) of the main spacecraft.

4.4.2 Spacecraft Stabilization and Attitude & Orbit Control Subsystem (AOCS) considerations

Three-axis stabilization is a measurement requirement for the ram direction instrumentation; two star-trackers are baselined

herein. Instrument pointing knowledge and pointing control requirements pose restrictions on the AOCS. The AOCS design 5

should take into account modes of vibration of the electric field and magnetic field booms. In addition, the release of the sub-

satellites and the use of propulsion will cause the spacecraft center of mass to move from its initial position; the use of six

(two per axis) mass trim mechanisms, driven on a nut rotor with a stepper motor, would allow the center of gravity of the

satellite to be re-adjusted after deep-dip manoeuvres and sub-satellite releases.

4.4.3 Propulsion Subsystem Considerations 10

The propulsion subsystem should be optimized to maximize the number of designed manoeuvres (21 perigee descents are

plotted in Fig. 10), while maintaining perigee and apogee to extend the mission lifetime. The propellant should not contain

constituents that could contaminate IMS and NMS measurements. Hybrid propulsion systems will be investigated, such as

have been proposed for the ESCAPE mission (Danduras, 2019, private communication): one will be used for perigee descent

and for manoeuvres, which can be low-Isp and relatively low-thrust, and a high-Isp propellant for ascent. 15

4.4.4 Radiation Environment Considerations

The highly elliptical orbit of the Daedalus mission means that the spacecraft will cross the inner radiation belt during apogee

passes. This becomes particularly significant above ~2,250 km. Thus special measures should be taken to utilize radiation-

hardened electronics and/or to shield all critical electronics. Both the main spacecraft and the sub-satellites need to be

radiation-hardened. A radiation monitor will be part of the Daedalus payload, in order to assist in safeguarding of the 20

spacecraft operations as well as to characterize the radiation environment.

4.4.5 Spacecraft Thermal Design

At perigee, and in particular during the perigee descents, enhanced free molecular heating rates can lead to significant

heating of the spacecraft, in particular at the ram direction. Adequate heat shields and an efficient heat dissipation system

should be used to mitigate potential overheating of the ram direction instruments. Electric field booms also need to be tested 25

under anticipated thermal and aerodynamic loads (combined) to ensure that they don't buckle or bend.


29

4.5 Relation to other Missions and Potential Synergies

The Daedalus mission will complement a series of very successful past missions, and will also by synergistic with a number

of planned and current missions; these are discussed in the following:

4.5.1 Relation to Past Missions

Several missions have performed in-situ measurements in the lower thermosphere-ionosphere, demonstrating the feasibility 5

of Daedalus measurements: Swarm is a current ESA EO three-spacecraft constellation mission to study the Earth’s magnetic

fields and currents flowing in the magnetosphere and ionosphere. Recently, the e-POP instrument package on Canada’s

Cassiope satellite was integrated with Swarm as the mission’s fourth element. Two of the Swarm satellites fly side-by-side

at 460 km and one at 530 km, and Swarm’s fourth element, e-POP, flies in an elliptical, polar orbit, with a perigee of 325 km

and apogee of 1,500 km; these are significantly higher than the 100-200 km transition region that is targeted by Daedalus. 10

Swarm measurements include magnetic fields, ion density, ion drift velocity, and non-gravitational accelerations like air-

drag, winds, Earth albedo and solar radiation pressure, however Swarm does not carry an ion or a neutral mass spectrometer,

and it also does not differentiate actual ion drifts from ExB ion drifts, which are crucial for Daedalus’ science objectives in

the LTI region. The Daedalus mission’s measurements will help extend to lower altitudes several scientific objectives of the

Swarm constellation mission, such as investigating electric currents in the magnetosphere and ionosphere and quantifying 15

the magnetic forcing of the upper atmosphere. MAVEN, an active Mars mission, successfully performs measurements in the

Martian thermosphere-ionosphere from a highly elliptical orbit, and the mission scenario also includes deep-dips into the

lower thermosphere, providing complete coverage of the Martian upper atmosphere and its interactions with the solar wind.

Measurements include ion and neutral composition, energetic particles and electric and magnetic fields, similarly to the

Daedalus concept, as well as neutral and ion winds, using the ion and neutral mass spectrometer. C-NOFS targeted the 20

effects of ionospheric activity on signals from communication and navigation satellites. Similarly to Daedalus, it performed

in-situ measurements of ion and neutral velocities as well as electric fields using 6 booms from an elliptical orbit; however it

had an equatorial orbit, and its perigee was 405 km, much higher than the altitude range targeted by Daedalus. C-NOFS also

lacked composition measurements. Cluster is an ESA mission consisting of four identical spacecraft flying in a tetrahedron-

like formation; it was launched in 2000 into an approximately 4 × 20 RE polar orbit with an inclination of about 87o and is 25

still operating. One of the four spacecraft, Tango (Cluster 2), made in 2009 the lowest dip into the ionosphere down to about

200 km altitude, performing field and ionospheric plasma measurements. In addition to these more recent missions, the

Atmosphere Explorers (AE) of the 1970s and the Dynamics Explorer (DE) mission of the 1980s also performed in-situ

measurements of density, ion drifts, multi-phase (neutral, ion) composition, and temperature structure down to the heart of

the transition region (e.g., perigee of ~150 km and deep-dips down to ~130 km by AE-C, and down to 280 km by DE). 30

These spacecraft lacked neutral wind measurements, with the exception of DE, which for the first time measured the vertical

motions of the local wind. It is also noted that the dynamic range of some of the key measurements of the AEs, such as mass


30

spectrometer composition, made the data interpretation difficult at low altitudes. Remote sensing missions of the LTI include

UARS (e.g., the WINDI instrument looked at winds and temperature at low and mid-latitudes, at 85 to 250 km) and TIMED

(which obtained O, O2, N2, ion density during daytime). These are among the primary sources of information on the LTI,

however for many key processes simultaneous measurements of all key geophysical variables are needed.

4.5.2 Synergy with ground-based instruments 5

An extensive network of ground-based instruments can provide supplementary context measurements in the ionosphere, and

be cross-calibrated in-situ by Daedalus. These include existing networks of Ionosondes, Incoherent Scatter Radars, Coherent

Scatter Radars, Auroral Imagers, Photometers and Fabry-Perot Interferometers. In particular the state-of-the-art volumetric

EISCAT_3D radar will be fully operational in 2022, well-timed with a potential launch of Daedalus in 2027/28, if selected.

The radar will provide electron density, electron and ion temperature and vector ion drift velocity between 70 and 1000 km 10

within a 3D cone with a diameter of 500 km at an altitude of 150 km (McCrea et al., 2015). Together, Daedalus and

EISCAT_3D would provide the “microscope-telescope” approach of combined in-situ and remote sensing measurements,

providing a powerful tool for LTI studies.

5 Discussion and Conclusions

5.1 On the Anticipated Impact of the Scientific Advances of Daedalus 15

The scientific advances anticipated from the mission are directly relevant to a number of societal issues: [1] Daedalus will

provide critical information of in-situ composition, and in particular CO2, to help address the response of the upper

atmosphere to global warming in the lower atmosphere and its role in energy balance processes. [2] Measurements that

Daedalus will perform in the LTI are essential for understanding the exosphere and modelling its altitude density profile and

its response to space weather events, as all exospheric models use parameters from this region as boundary conditions. [3] 20

Furthermore during geomagnetic storms and substorms, currents with increased amplitudes close through the LTI, producing

enhanced Joule (ohmic) heating (Palmroth et al., 2005; Aikio et al., 2012) and leading to significant enhancements in neutral

density, which in turn results in enhanced satellite drag. Daedalus will provide critical measurements for Joule heating

estimates that can be used as anchor-points in global circulation models. [4] Space weather effects enhance ionospheric

scintillation of the Global Navigation Satellite System (GNSS) signals, which severely degrades positional accuracy and 25

affects performance of radio communications and navigation systems (Xiong et al., 2016); Daedalus will measure in-situ

plasma parameters that are involved in GNSS signal scintillation. [5] Sudden enhancements in the current system that closes

within the LTI induce GICs on the ground, the impact of which on power transformers in electrical power systems has, in

occasions, been catastrophic (Pulkkinen et al., 2017) and is considered a threat to technology-based societies, should an

extreme solar event occur. Daedalus will measure in-situ the currents that produce GICs, and will thus assist in the accurate 30

modelling of GICs in response to geomagnetic activity. [6] Energetic proton and electron precipitation has a role in


31

mesospheric ozone destruction, large enough to be important at the atmospheric and climate level (Andersson et al., 2014).

So far it has been difficult to assess the impact of the role due to insufficient energy spectrum associated with the

precipitation. Daedalus will provide the necessary EPP energy spectrum, together with local composition, to directly assess

the role of EPP in upper atmosphere chemistry.

Despite its significance to the above societal issues, the LTI region is the least measured and least understood of all 5

atmospheric regions. The continuous and ever-increasing presence of mankind in space and the importance of the behaviour

of this region to multiple issues related to aerospace technology, such as orbital calculations, vehicle re-entry, space debris

lifetime etc., together with its importance in global energy balance processes and in the production of GICs and GNSS

scintillations make its extensive study a pressing need. Daedalus responds to the above societal challenges by providing

ground-breaking measurements in a region that has been vastly under-sampled, via innovative orbital manoeuvres and sub-10

satellite deployments. These observations should be sustained so as to resolve the seasonal variability of key LTI

phenomena, as described above, while providing sufficient temporal coverage to resolve the time-scales of dynamic events

that lead to upper atmosphere heating. Measurements will be synthesised from a set of individual instruments, each of which

provides critical parameters towards the science results. Daedalus will also have synergy with many current and future

scientific space missions, such as MEME-X, AWE, TRACERS, GOLD, ICON, GDC and DYNAMIC. 15

5.2 On the Uniqueness and Complementarity of Daedalus

5.2.1 Uniqueness: Other means for addressing the mission requirements

Some of the required parameters can be measured by ground instrumentation, but Joule heating and EPP cannot be derived

accurately based on those measurements, as all required parameters must be measured simultaneously at the same location.

In particular, neutral density and wind estimations from the ground are very problematic within the 100-200 km altitude 20

range. Optical methods based on Fabry-Perot interferometers exist for neutral wind, but those require non-cloudy conditions

and even then, provide only height-averaged measurements from typically 1 or 2 specific altitudes (e.g. Oyama et al., 2018).

In addition, ground stations are inherently limited to a specific location, whereas a spacecraft will eventually cover all local

times and latitudes. The uncertainty in obtaining accurate Joule heating estimates between various methods is demonstrated

in Fig. 5, where different methods vary in their estimates by up to 500% (Palmroth et al., 2005). An in-situ mission with all 25

necessary measurements will provide reference points against which different models and methodologies can be validated

and the role of neutral dynamics can be quantified.

5.2.2 Complementarity: Upper Atmosphere activities of other national and international bodies.

On June 28, 2017, NASA has selected nine proposals under its Explorers Program; of these missions, three are directly

related to processes in the upper atmosphere, and will complement the science results of Daedalus: MEME-X (Mechanisms 30

of Energetic Mass Ejection – eXplorer) will map the universal physical processes of the lower geospace system that control


32

the mass flux through the upper atmosphere to space potentially transforming our understanding of how ions leave Earth’s

atmosphere. AWE (Atmospheric Waves Experiment) will investigate how atmospheric gravity waves impact the transport of

energy and momentum from the lower atmosphere, a fundamental question in Heliophysics. TRACERS will study

interactions between the solar wind and the magnetosphere from an altitude of 750 km, focusing on cusp electrodynamics.

The timeframe for the development of these three missions is well timed with the present EE-10 call and these missions can 5

offer excellent complementarity with the measurements of Daedalus. Two currently active NASA missions are targeting the

thermosphere: GOLD (Global-scale Observations of the Limb and Disk), operated by NASA, explores the upper atmosphere

through full-disk UV images of Earth from geostationary orbit, through which scientists can determine the temperature and

relative amounts of different chemical elements present in the neutral gases (O and N2), which, in turn, help show how the

neutral gases shape characteristics of the ionosphere. GOLD was launched on January 25, 2018. ICON (Ionospheric 10

Connection Explorer) will study the ionosphere and neutral upper atmosphere in conjunction with GOLD: while GOLD flies

in geostationary orbit, ICON will fly 560 km above Earth, where it can gather close-up images of this region. ICON is

prepared for launch in 2019. Finally, NASA’s next science targets, as outlined in the Heliophysics Decadal Survey, include

two reference missions: GDC (Geospace Dynamics Constellation), a mission to understand how the atmosphere, ionosphere,

and magnetosphere are coupled as a system and to understand how this system regulates the response of all geospace to 15

external energy input; and DYNAMIC (Dynamical Neutral Atmosphere-Ionosphere Coupling), a mission targeting the

fundamental processes that underlie the transfer of energy and momentum into the Ionosphere-Thermosphere system and to

measure the thermospheric and ionospheric variability that lower atmospheric waves cause at higher altitudes.

These missions highlight a new interest for the last exploration barrier, the LTI. However none of these missions plan to

study in-situ the key transition region between 100-200 km, where most energy balance processes maximize and where most 20

abrupt variations exist. Daedalus will provide unique and unprecedented measurements in the upper atmosphere to

complement and calibrate remote sensing measurements and help develop accurate models of the upper atmosphere. With

Daedalus, ESA will assume international leadership in studying the LTI and its processes.

5.2 On the Degree of innovation and the Advancement of EO Capabilities of Daedalus

An innovative technology of the Daedalus mission concept is the release on-command of sub-satellites from a mother-ship; 25

this can be used in concepts such as the release on-demand of sub-satellites that can form a constellation for Earth

Observation / remote sensing / communications or other applications. Another innovation is the performance of orbital

manoeuvres and perigee descents in combination with an efficient propulsion system for orbital maintenance, in order to

achieve the lowest perigee achieved up to now by an Earth Observation satellite. Daedalus measurements will help advance

upper atmosphere modeling: EPP data along the s/c track will be used to drive ionospheric and thermospheric models such 30

as GLOW (Solomon, 2017) and satellite track models (Emery et al., 1985; Deng et al., 1995; Wu et al., 1996), to calculate

the ionization, heating, and composition changes, which can be compared with observations of thermospheric temperatures.

These models can use along-track data to derive the global EPP heating. A comparison with observations of thermospheric


33

temperature can lead to estimates of global Joule heating, based on the differences between EPP model and observations.

Daedalus data will be assimilated into TIEGCM and other ionosphere-thermosphere models to provide accurate calculations

of global Joule heating and EPP heating. At high latitudes, Daedalus data will be used to build AMIE (Assimilative Mapping

of Ionospheric and Electrodynamics) convection maps (Richmond, 1992). Thus, an advancement of EO capabilities is that

Daedalus measurements will enable the calibration, assimilation and accurate driving of upper atmosphere models. Daedalus 5

will provide critical information regarding EPP and Joule heating, and it will distinguish between heating sources, something

that has not been possible to date.

5.3 Conclusions

The Daedalus mission concept comes at a moment in geophysical sciences when space agencies and international space

committees recognize and emphasize the need and the importance of studying the LTI. Understanding the LTI matters in a 10

number of domains, such as orbital calculations, vehicle re-entry, space debris lifetime etc., together with its importance in

global energy balance processes and in the production of Geomagnetically Induced Currents (GICs), which are a threat to

power transformers and through that to society as a whole. In addition, the LTI acts as a boundary condition to atmospheric

models, and its proper characterization is critical for the accurate modeling of a number of processes; with the high level of

detail that is required in global climate models, key unknown factors such as the energy balance in the LTI need to be 15

resolved. At the same time, linking magnetospheric electrodynamics models with ionospheric and atmospheric models relies

on accurate representation of key processes in the LTI, such as Joule heating, and the correct quantification of key variables,

such as conductivities and the particle energy spectrum.

The Daedalus mission concept is also well timed with a number of international space missions that are targeting to measure

key properties in the LTI by means of remote sensing; these include the recently selected MEME-x, AWE and TRACERS, 20

the recently launched GOLD and the soon-to-be launched ICON mission. NASA’s decadal survey includes two reference

missions that are also targeting ionosphere-thermosphere processes: GDC and DYNAMIC. Furthermore, the state-of-the-art

volumetric EISCAT_3D radar (one of the Large-Scale European Research Infrastructures selected by the European Strategy

Forum on Research Infrastructures for the next 20-30 years) will be fully operational in 2022, well timed with Daedalus, and

will provide time-series of ionospheric parameters over Northern Scandinavia. Daedalus will provide in-situ validation and 25

cross-calibration of these parameters and will also enable extension of these measurements along its orbit. With regard to

technical constraints, the Daedalus mission concept builds on a series of very successful missions with features that are

similar to those of Daedalus, such as the aerodynamic shape of GOCE and its use of propulsion for orbit maintenance, the

innovative Swarm missions with instrumentation of extreme precision and direct relevance to upper atmosphere scientific

issues and the deep-dips of MAVEN into the thermosphere of Mars; these missions have successfully demonstrated key 30

technologies for the potential implementation of Daedalus.


34

References

Ahn, B.H., Akasofu, S.I. and Kamide, Y.: The Joule heat production rate and the particle energy injection rate as a function

of the geomagnetic indices AE and AL, J. Geophys. Res., 88, 6275–6287, 1983.

Aikio, A. T., Cai, L. and Nygrén, T.: Statistical distribution of height-integrated energy exchange rates in the ionosphere, J.

Geophys. Res., 117, A10325, doi:10.1029/2012JA018078, 2012. 5

Amm, O., Aksnes, A., Stadsnes, J., Østgaard, N., Vondrak, R. R., Germany, G. A., Lu, G., and Viljanen, A.: Mesoscale

ionospheric electrodynamics of omega bands determined from ground-based electrodynamic and satellite optical

observations, Ann. Geo- phys., 23, 325–342, 2005.

Anderson, B. J., Takahashi, K., and Toth, B. A.: Sensing global Birkeland currents with Iridium engineering magnetometer

data, Geophys. Res. Lett., 27, 4045–4048, 2000. 10

Andersson, L., Ergun, R. E., Delory, G. T., Eriksson, A., Westfall, J., Reed, H., McCauly, J., Summers, D. and Meyers, D.:

The Langmuir Probe and Waves (LPW) Instrument for MAVEN, vol. 195, pp. 173-198, doi:10.1007/s11214-015-0194-3,

2015.

Andersson, M. E., Verronen, P. T., Rodger, C. J., Clilverd, M. A., and Seppälä, A.: Missing driver in the Sun–Earth

connection from energetic electron precipitation impacts mesospheric ozone, Nature Comm., doi:10.1038/ncomms6197, 15

2014.

Appleton, E. V.: Two anomalies in the ionosphere, Nature, 157, 691, 1946.

Auster, H. U., Apathy, I., Berghofer, G., Remizov, a., Roll, R., Fornacon, K. H., Glassmeier, K. H., et al.: ROMAP: Rosetta

Magnetometer and Plasma Monitor. Space Science Reviews, 128(1-4), 221-240. doi:10.1007/s11214-006-9033-x, 2007.

Auster, H. U., Glassmeier, K. H., Magnes, W., Aydogar, O., Baumjohann, W., Constantinescu, D., Fischer, D., et al.: The 20

THEMIS Fluxgate Magnetometer. Space Science Reviews, 141(1-4), 235-264. doi:10.1007/s11214-008-9365-9, 2008.

Auster, H. U., Richter, I., Glassmeier, K. H., Berghofer, G., Carr, C. M., & Motschmann, U.: Magnetic field investigations

during ROSETTA’s 2867 Šteins flyby. Planetary and Space Science, 58(9), 1124-1128 doi:10.1016/j.pss.2010.01.006, 2010.

Bale, S. D., Ullrich, R., Goetz, K., et al.: The Electric Antennas for the STEREO/WAVES Experiment, vol. 136, pp. 529-

547, doi:10.1007/s11214-007-9251-x, 2008. 25

Birkeland, Kristian (1908). The Norwegian Aurora Polaris Expedition 1902-1903. New York and Christiania (now Oslo): H.

Aschehoug & Co. out-of-print, full text online at https://archive.org/details/norwegianaurorap01chririch


35

Burchill, J.K., D.J. Knudsen, B.J.J. Bock, R.F. Pfaff, D.D. Wallis, J.H. Clemmons, S.R. Bounds, H. Stenbaek-Nielsen: Core

ion interactions with BB ELF, lower hybrid, and Alfvén waves in the high-latitude topside ionosphere. J. Geophys. Res. 109,

A01219, doi:10.1029/2003JA010073, 2004.

Burchill, J.K., D.J. Knudsen, J.H. Clemmons, K. Oksavik, R.F. Pfaff, C.T. Steigies, A.W. Yau, T.K. Yeoman: Thermal ion

upflow in the cusp ionosphere and its dependence on soft electron energy flux. J. Geophys. Res. 115, A05206, 5

doi:10.1029/2009JA015006, 2010.

Burchill, J.K., J.H. Clemmons, D.J. Knudsen, M. Larsen, M.J. Nicolls, R.F. Pfaff, D. Rowland, L. Sangalli, High-latitude E

region ionosphere-thermosphere coupling: A comparative study using in situ and incoherent scatter radar observations. J.

Geophys. Res. 117, A02301, doi:10.1029/2011JA017175, 2012.

Cai, L., Aikio, A. T., and Nygrén, T.: Height-dependent energy exchange rates in the high-latitude E region ionosphere, J. 10

Geophys. Res. Space Physics, 118, doi:10.1002/2013JA019195, 2013.

Carlson, C. W., Curtis, D. W., Paschmann, G., and Michael, W.: An instrument for rapidly measuring plasma distribution

functions with high resolution, Adv. Space Res., 2, 67–70, 1983.

Chun, F. K., Knipp, D. J., McHarg, M. G., Lu, G., Emery, B. A., Vennerstrom, S., and Troshichev, O. A.: Polar cap index as

a proxy for hemispheric Joule heating, Geophys. Res. Lett., 26, 1101– 1104, 1999. 15

Codrescu, M. V., Fuller-Rowell, T. J., and Foster, J. C.: On the importance of E-field variability for Joule heating in the

high-latitude thermosphere, Geophys. Res. Lett., vol. 22, 17, doi:10.1029/95GL01909, 1995.

Codrescu, M. V., Fuller-Rowell, T. J., Roble, R. G., and Evans, D. S.: Medium energy particle precipitation influences on

the mesosphere and lower thermosphere, J. Geophys. Res., 102, 19,977, 1997.

Cully, C. M., Ergun, R. E., and Eriksson, A. I.: Electrostatic structure around spacecraft in tenuous plasmas, Journal of 20

Geophysical Research (Space Physics), vol. 112, pp. A09211, doi:10.1029/2007JA012269, 2007.

Cully, C. M., Ergun, R. E., Stevens, K., Nammari, A. and Westfall, J.: The THEMIS Digital Fields Board, vol. 141, pp. 343-

355, doi:10.1007/s11214-008-9417-1, 2008.

Deng, W., Killeen, T. L., Burns, A. G., Johnson, R. M., Emery, B. A., Roble, R. G., Winningham, J. D., and Gary, J. B.:

One-dimensional hybrid satellite track model for the Dynamics Explorer 2 (DE 2) satellite, J. Geophys. Res., 100, N A2, 25

1611-1624, doi:94JA02075, 1995.

Dhadly, M. S., Emmert, J. T., Drob, D. P., Conde, M. G., Doornbos, E., Shepherd, G. G.,... Ridley, A. J.: Seasonal

dependence of geomagnetic active-time northern high-latitude upper thermospheric winds, J. Geophys. Res., Space Physics,

123, 739–754. https://doi.org/10.1002/2017JA024715, 2018.


36

Doss, N., Fazakerley, A. N., Mihaljčić, B., Lahiff, A. D., Wilson, R. J., Kataria, D., Rozum, I., Watson, G., and Bogdanova,

Y.: In-flight calibration of the Cluster PEACE sensors, Geosci. Instrum. Method. Data Syst., 3, 59-70, doi:10.5194/gi-3-59-

2014, 2014.

Doornbos, E., van den Ijssel, J., Lühr, H., Förster, M., Koppenwallner, G: Neutral Density and Crosswind Determination

from Arbitrarily Oriented Multiaxis Accelerometers on Satellites, J. Spacecraft and Rockets, Vol. 47, No. 4, 5

doi:10.2514/1.48114, 2010.

Dunlop, M. W., Balogh, A., Glassmeier, K. H., and Robert, P.: Four-point Cluster application of magnetic field analysis

tools: The Curlometer, J. Geophys. Res., 107, 1384–1397, 2002.

Earle, G. D., J. H. Klenzing, P. A Roddy, W. A. Macaulay, M. D. Perdue, and E. L. Patrick: A new satellite-borne neutral

wind instrument for thermospheric diagnostics, Rev. Sci. Instrum. 78, 114501 (2007); https://doi.org/10.1063/1.2813343, 10

2007.

Earle, G. D., R. L. Davidson, R. A. Heelis, W. R. Coley, D. R. Weimer, J. J. Makela, D. J. Fisher, A. J. Gerrard, and J.

Meriwether: Low latitude thermospheric responses to magnetic storms, J. Geophys. Res. Space Physics, 118, 3866–3876,

doi:10.1002/jgra.50212. 2013.

Emery et al.: Thermospheric and ionospheric structure of the southern hemisphere polar cap on October 21, 1981, as 15

determined from Dynamics Explorer 2 satellite data, J. Geophys. Res., 90, A7, 6553-6566 doi:4A8350, 1985.

Ergun, R. E., Tucker, S., Westfall, J., Goodrich, K. A., Malaspina, D. M., Summers, D., Wallace, J., Karlsson, M., Mack, J.,

Brennan, N., Pyke, B., Withnell, P., Torbert, R., Macri, J., Rau, D., Dors, I., Needell, J., Lindqvist, P.-A., Olsson, G., Cully,

C. M.: The Axial Double Probe and Fields Signal Processing for the MMS Mission, vol. 199, pp. 167-188,

doi:10.1007/s11214-014-0115-x, 2016. 20

ESA’s EO Swarm mission: https://earth.esa.int/web/guest/missions/esaoperational-eo-missions/swarm

Fang H., and Cheng, C.: Retarding Potential Analyzer (RPA) for sounding rocket, in: An Introduction to Space

Instrumentation, edited by KI Oyama and CZ Cheng, pp. 139–153, 2013.

Fang, X., Randall, C. E., Lummerzheim, D., Wang, W., Lu, G., Solomon, S. C., and Frahm, R. A.: Parameterization of

monoenergetic electron impact ionization, Geophys. Res. Lett., 37, L22,106, doi:10.1029/2010GL045406, 2010. 25

Fok, M. C., et al.: Global ENA IMAGE Simulations. In: Burch J.L. (eds) Magnetospheric Imaging — The Image Prime

Mission. Springer, Dordrecht, 2003.

Foster, J. C., St.-Maurice, J.-P., and Abreu, V. J.: Joule heating at high latitudes, J. Geophys. Res., 88, 4885– 4896, 1983.

Fratter, I., Léger, J.-M., Bertrand, F., Jager, T., Hulot, G., Brocco, L., Vigneron, P.: Swarm Absolute Scalar Magnetometers

first in-orbit results Acta Astronautica, 121, pp. 76-87. Cited 9 times, doi: 10.1016/j.actaastro.2015.12.025, 2016. 30


37

Ganushkina, N. Y., M. W. Liemohn, O. Amariutei, I. A. Daglis, I. Dandouras, S. Dubyagin, D. L. De Zeeuw, Y. Ebihara, R.

Ilie, R. Katus, M. Kubyshkina, S. E. Milan, S. Ohtani, N. Ostgaard, J. P. Reistad, P. Tenfjord, F. Toffoletto, and S. Zaharia:

Defining and resolving current systems in geospace, Ann. Geophys., doi:10.5194/angeo-33-1369-2015, 2015.

Gary, J. B., R. A. Heelis, W. B. Hanson, and J. A. Slavin: Field aligned Poynting flux observations in the high latitude

ionosphere, J. Geophys. Res., 99, 11,417– 11,427, 1994. 5

Gordiets, B. F., Y. N. Kulikov, M. N. Markov, and M. Y. Marov: Numerical modeling of the thermospheric heat budget, J.

Geophys. Res., 87, 4504–4514, doi:10.1029/JA087iA06p04504, 1982.

Hanson, W. B., U. Ponzi, C. Arduini, and M. DiRuscio: A satellite anemometer, J. Astro. Sci., 40, 429, 1992.

Hanson, W., R. Heelis, R. Power, C. Lippincott, D. Zuccaro, B. Holt, L. Harmon, and S. Sanatani: The retarding potential

analyzer for dynamics explorer-b, Space Science Instrumentation, vol. 5, pp. 503–510, 1981. 10

Hatch, W. S.: Plasma velocity vector instruments for small satellites, Master’s thesis, Utah State University, Logan, UT,

2016.

Hedin, A. E.: Extension of the MSIS Thermospheric Model into the middle and lower atmosphere, J. Geophys. Res., 96(A2),

1159–1172, doi:10.1029/90JA02125, 1991.

Huba, J. D., R. W. Schunk, and Khazanov: Modeling the Ionosphere-Thermosphere, John Wiley & Sons, vol. 201, 2014. 15

Kivelson, Margaret G., and Christopher T. Russell: Introduction to Space Physics, Cambridge atmospheric and space science

series, Cambridge University Press. ISBN, 0521457149, 9780521457149, 1995.

Knudsen, D. J., J. K. Burchill, K. Berg, T. Cameron, G. A. Enno, C. G., Marcellus, E. P. King, I. Wevers, and R. A. King: A

low‐energy charged particle distribution imager with a compact sensor for space applications, Rev. Sci. Instrum. , 74, 202–

211, doi:10.1063/1.1525869, 2003. 20

Knudsen, D. J., et al.: Lower‐hybrid cavity density depletions as a result of transverse ion acceleration localized on the

gyroradius scale, J. Geophys. Res., 109, A04212, doi:10.1029/2003JA010089, 2004.

Kwak, Y.-S., and Richmond, A. D.: An analysis of the momentum forcing in the high-latitude lower thermosphere,

J. Geophys. Res., 112, A01306, doi:10.1029/2006JA011910, 2007.

Laštovička, J.: Trends in the upper atmosphere and ionosphere: Recent progress, J. Geophys. Res. Space Physics, 118, 3924–25

3935, doi:10.1002/jgra.50341, 2013.

Léger, J.-M., Jager, T., Bertrand, F., Hulot, G., Brocco, L., Vigneron, P., Lalanne, X., (...), Fratter, I.: In-flight performance

of the Absolute Scalar Magnetometer vector mode on board the Swarm satellites, Earth, Planets and Space, 67 , doi:

10.1186/s40623-015-0231-1, 2015.


38

Lin, Z. W., C. K. Chao, J. Y. Liu, C. M. Huang, Y. H. Chu, C. L. Su, Y. C. Mao, and Y. S. Chang: Advanced Ionospheric

Probe scientific mission onboard FORMOSAT-5 satellite. Terr. Atmos. Ocean. Sci., 28, 99-110, doi: 10.3319/

TAO.2016.09.14.01(EOF5), 2017

MacManus D. H., C. J. Rodger, M. Dalzell, A. W. P. Thomson, M. A. Clilverd, T. Petersen, M. M. Wolf, N. R. Thomson,

and T. Divett: Long-term geomagnetically induced current observations in New Zealand: Earth return corrections and 5

geomagnetic field driver, Space Weather, 15, 1020–1038, doi:10.1002/ 2017SW001635, 2017.

Malaspina, D. M., Ergun, R. E., Bolton, M., Kien, M., Summers, D., Stevens, K., Yehle, A., Karlsson, M., Hoxie, V. C.,

Bale, S. D., Goetz, K.: The Digital Fields Board for the FIELDS instrument suite on the Solar Probe Plus mission: Analog

and digital signal processing, Journal of Geophysical Research (Space Physics), vol. 121, pp. 5088-5096,

doi:10.1002/2016JA022344, 2016. 10

McCrea, I., Aikio, A., Alfonsi, L., Belova, E., Buchert, S., Clilverd, M., Engler, N., Gustavsson, B., Heinselman, C., Kero,

J., Kosch, M., Lamy, H., Leyser, T., Ogawa, Y., Oksavik, K., Pellinen-Wannberg, A., Pitout, F., Rapp, M., Stanislawska, I.,

and Vierinen, J.: The science case for the EISCAT_3D radar, Progress in Earth and Planetary Science, 2:21,

https://doi.org/10.1186/s40645-015-0051-8, 2015.

Mozer, F. S.: DC and low-frequency double probe electric field measurements in space, Journal of Geophysical Research 15

(Space Physics), vol. 121, A10, pp. 10, doi:10.1002/2016JA022952, 2016.

Ogawa, Y., T. Motoba, S. C. Buchert, I. Häggström, and S. Nozawa: Upper atmosphere cooling over the past 33 years,

Geophys. Res. Lett., 41, 5629–5635, doi:10.1002/2014GL060591, 2014.

O'Hanlon, J. F.: A User's Guide to Vacuum Technology, 2nd ed., 95, John Wiley, New York, 1989.

Olsson, A., P. Janhunen, T. Karlsson, N. Ivchenko, and L. G. Blomberg: Statistics of Joule heating in the auroral zone and 20

polar cap using Astrid-2 satellite Poynting flux, Ann. Geophys., 22: 4133–4142, 2004.

Østgaard, N., Germany, G., Stadsnes, J. and Vondrak, R. R.: Energy analysis of substorms based on remote sensing

techniques, solar wind measurements, and geomagnetic indices, J. Geophys. Res., 107 (A9), 1233,

doi:10.1029/2001JA002002, 2002.

Palmroth, M., Janhunen, P., Pulkkinen, T. I., and Koskinen, H. E. J.: Ionospheric energy input as a function of solar wind 25

parameters: global MHD simulation results, Ann. Geophys., 22, 549–566, 2004.

Palmroth, M., P. Janhunen, T. I. Pulkkinen, A. Aksnes, G. Lu, et al.: Assessment of ionospheric Joule heating by GUMICS-4

MHD simulation, AMIE, and satellite-based statistics: towards a synthesis. Annales Geophysicae, European Geosciences

Union, 2005, 23 (6), pp. 2051-2068, 2005.


39

Palmroth, M., P. Janhunen, G.A. Germany, D. Lummerzheim, K. Liou, D.N. Baker, C. Barth, A.T. Weatherwax, and J.

Watermann: Precipitation and total power consumption in the ionosphere: Global MHD simulation results compared with

Polar and SNOE observations, Ann. Geophys. 24, pp. 861–872, 2006.

Paschalidis N., S. L. Jones, M. Rodriguez et al.: A Compact Ion Neutral Mass Spectrometer for the ExoCube Mission, 6th

European CubeSat Symposium, Estavayet, Switzerland, 2014. 5

Paschalidis N., S. L. Jones, M. Rodriguez et al. : A compact Ion Neutral Mass Spectrometer for ionospheric measurements –

Flight Demo on Exocube and Dellingr missions, under submission, RSI, 2019

Pulkkinen A., E. Bernabeu, A. Thomson, A. Viljanen, R. Pirjola, D. Boteler, J. Eichner, P. J. Cilliers, D. Welling, N. P.

Savani, et al.: Vol: 15,; Pages: 828–856; DOI: 10.1002/2016SW001501, 2017.

Qian, L., J. Laštovička, R. G. Roble, and S. C. Solomon: Progress in observations and simulations of global change in the 10

upper atmosphere, J. Geophys. Res., 116, A00H03, doi:10.1029/2010JA016317, 2011.

Randall, C. E., V. L. Harvey, C. S. Singleton, S. M. Bailey, P. F. Bernath, M. Codrescu, H. Nakajima, and J. M. Russell III:

Energetic particle precipitation effects on the Southern Hemisphere stratosphere in 1992–2005, J. Geophys. Res., 112,

D08308, doi:10.1029/2006JD007696, 2007.

Richmond, A. D.: Assimilative mapping of ionospheric electrodynamics, Adv. Space Res., Vol 12, No 6, pp (6)69-(6)68, 15

1992.

Richmond, A. D.: Ionospheric Electrodynamics, in Handbook of Atmospheric Electrodynamics, Vol. II (H. Volland, ed.),

CRC Press, Boca Raton, Florida, 249-290, 1995.

Rishbeth, H., and R. G. Roble: Cooling of the upper atmosphere by enhanced greenhouse gases—Modelling of

thermospheric and ionospheric effects, Planet. Space Sci., 40, pp. 1011–1026, doi:10.1016/0032-0633(92)90141-A, 1992. 20

Ritter, P., Lühr, H., Rauberg, J.: Determining field-aligned currents with the Swarm constellation mission, Earth Planet Sp

65: 9. https://doi.org/10.5047/eps.2013.09.006, 2013.

Rodger, C. J., Clilverd, M. A., Green, J. C., and Lam, M. M.: Use of POES SEM-2 observations to examine radiation belt

dynamics and energetic electron precipitation into the atmosphere, J. Geophys. Res., 115, doi:10.1029/2008JA014023, 2010.

Rosenqvist, L., S. Buchert, H. Opgenoorth, A. Vaivads, and G. Lu (2006): Magnetospheric energy budget during huge 25

geomagnetic activity using Cluster and ground-based data, J. Geophys. Res., 111, A10211, doi:10.1029/2006JA011608.

Sangalli, L., D.J. Knudsen, M.F. Larsen, T. Zhan, R.F. Pfaff, D. Rowland, Rocket-based measurements of ion velocity,

neutral wind, and electric field in the collisional transition region of the auroral ionosphere. J. Geophys. Res. 114, A4, 2009.


40

Sarris, T. E., et. al.: Feasibility Study for a Low-Flying Spacecraft for the Exploration of the MLTI Region, Technical

Report, ESA/ESTEC, CN 20991, 2010.

Sarris, T. E., et. al.: Electrodynamics Study of the Upper Atmosphere in Support to Future MLTI Missions, Technical

Report, ESA/ESTEC, CN 4000104174/11/NL/AF, 2013.

Sauvaud, J.-A., Larson, D., Aoustin, C., Curtis, D., Médale, J.-L., Fedorov, A., Rouzaud, J., Luhmann, J., Moreau, T., 5

Schröder, P., Louarn, P., Dandouras, I., and Penou, E.: The IMPACT Solar Wind Electron Analyzer (SWEA), Space Sci.

Rev., 136: 227–239, doi: 10.1007/s11214-007-9174-6, 2008.

Scarf, F. L., Fredricks, R. W., Gurnett, D. A., and Smith, E. J.: The ISEE-C Plasma Wave Investigation, IEEE Transaction

on Geoscience Electronics, Vol. GE-16, No 3, July 1978.

Semeter, J., and F. Kamalabadi: Determination of primary electron spectra from incoherent scatter radar measurements of 10

the auroral E region, Radio Sci., 40, RS2006, doi:10.1029/2004RS003042, 2005.

Seppälä , A., P. T. Verronen, E. Kyrölä , S. Hassinen, L. Backman, A. Hauchecorne, J. L. Bertaux, and D. Fussen: Solar

proton events of October–November 2003: Ozone depletion in the Northern hemisphere polar winter as seen by

GOMOS/Envisat, Geophys. Res. Lett., 31, L19107, doi:10.1029/2004GL021042, 2004.

Seppälä, A., C. E. Randall, M. A. Clilverd, E. Rozanov, and C. J. Rodger: Geomagnetic activity and polar surface air 15

temperature variability, J. Geophys. Res., 114, A10312, doi:10.1029/2008JA014029, 2009.

Sinnhuber, M., Nieder, H. & Wieters, N. Surv Geophys: Energetic Particle Precipitation and the Chemistry of the

Mesosphere/Lower Thermosphere 33: 1281. https://doi.org/10.1007/s10712-012-9201-3, 2012.

Solomon, S. C., L. Qian, and R. G. Roble: New 3-D simulations of climate change in the thermosphere, J. Geophys. Res.

Space Physics, 120, 2183–2193, doi:10.1002/2014JA020886, 2015. 20

Solomon, S. C.: Global modeling of thermospheric airglow in the far ultraviolet, J. Geophys. Res. Space Physics, 122, 7834–

7848, doi:10.1002/ 2017JA024314, 2017.

Sutton, E. K., R. S. Nerem, and J. M. Forbes: Density and Winds in the Thermosphere Deduced from Accelerometer Data,

Journal of Spacecraft and Rockets, Vol. 44, No. 6, pp. 1210-1219. https://doi.org/10.2514/1.28641, 2007.

Swenson, A. P.: The Field-Programmable Gate Array Design of the Gridded Retarding Ion Distribution Sensor. All Graduate 25

Theses and Dissertations. 6876, https://digitalcommons.usu.edu/etd/6876, 2017.

Thayer, J. P., and J. Semeter: The convergence of magnetospheric energy flux in the polar atmosphere, J. Atmos. Sol. Terr.

Phys., 66, 807–824, 2004.


41

Trotignon, J. G., D'eau, P. M. E., Rauch, J. L., et al.: The Whisper Relaxation Sounder Onboard Cluster: A Powerful Tool

for Space Plasma Diagnosis$^{1, 2$ around the Earth, Cosmic Research, vol. 41, pp. 345-348, 2003.

Trotignon, J.G., Michau, J.L., Lagoutte, D. et al.: RPC-MIP: the Mutual Impedance Probe of the Rosetta Plasma

Consortium, Space Sci Rev., 128: 713. https://doi.org/10.1007/s11214-006-9005-1, 2007.

Vasyliūnas, V. M., and P. Song: Meaning of ionospheric Joule heating, J. Geophys. Res., 110, A02301, 5

doi:10.1029/2004JA010615, 2005.

Wu, Q., T. L. Killeen, W. Deng, A. G. Burns, J. D. Winningham, N. W. Spencer, R. A. Heelis, and W. B. Hanson: Dynamics

Explorer 2 satellite observations and satellite track model calculations in the cusp/cleft region, J. Geophys. Res., 101, N A32,

5329-5342, doi:95JA01819, 1995.

Wygant, J. R., Bonnell, J. W., Goetz, et al.: The Electric Field and Waves Instruments on the Radiation Belt Storm Probes 10

Mission, vol. 179, pp. 183-220, doi:10.1007/s11214-013-0013-7, 2013.

Xiong C, Stolle C, Lühr H.: The Swarm satellite loss of GPS signal and its relation to ionospheric plasma irregularities,

Space Weather, Vol. 14, pp. 563-577. DOI: 10.1002/2016SW001439, 2016.

Yizengaw, E., & Essex, E. A.: Use of GPS signals to study Total Electron Content of the ionosphere during the geomagnetic

storm on 22 September 1999.Victoria: Cooperative research center for satellite systems, 1999. 15

Yuan, Z., et al.: Influence of precipitating energetic ions caused by EMIC waves on the subauroral ionospheric E region

during a geomagnetic storm, J. Geophys. Res. Space Physics,119,8462–8471, doi:10.1002/2014JA020303, 2014

Zhang, X. X., C. Wang, T. Chen, Y. L. Wang, A. Tan, T. S. Wu, G. A. Germany, and W. Wang: Global patterns of Joule

heating in the high-latitude ionosphere, J. Geophys. Res., 110, A12208, doi:10.1029/2005JA011222, 2005.

Zoennchen, J. H., U. Nass, H. J. Fahr, and J. Goldstein: The response of the H geocorona between 3 and 8 Re to 20

geomagnetic disturbances studied using TWINS stereo Lyman-data, Ann. Geophys., doi:10.5194/angeo-35-171-2017, 2017.


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Tables

Source Energy (W/m2) Altitude Solar EUV Radiation 0.003 100 – 500 km

Precipitating Particles

-‐-‐ Magnetospheric Protons -‐-‐ Magnetospheric Electrons

0.001 – 0.006 0.003 – 0.030

100 – 130 km 70 – 130 km

Joule Heating

-‐-‐ E = 1-‐100 mV/m 0.000014 – 0.140 100 – 500 km

Solar Wind

-‐-‐ Kinetic 1/2pυ3

-‐-‐ Electromagnetic ExB/μ0

0.00030

0.00003

N/A

Table 1: Main energy inputs and ranges in the LTI region.


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Instrument Measurement Dynamic Range Accuracy, sensitivity Ion Drift Meter (IDM) & Retarding Potential Analyzer (RPA), or Thermal Ion Imager (TII)

Ion drifts Ion density Ion Temperature

±4 km/s [along track and cross track]

100 m/s [along track and cross track]

Ram Wind Sensor (RWS) & Cross-‐track Wind Sensor (CWS)

Ram neutral winds Cross-‐track neutral winds Differential pressure Neutral temperature

±1 km/s [along track and cross track]

Accuracy ±10 m/s, sensitivity ±3 m/s [along track] Accuracy ±5 m/s, sensitivity ±2 m/s [cross-‐track]

Accelerometer (ACC) Neutral density Wind velocity Thrust of propulsion syst.

10-‐7 g to 10-‐3 g Accuracy ±10% at 500km, ±2% below 200km Sensitivity 10-‐7 g ±3% max systematic error due to uncertainty in drag coefficient

Energetic Particle Detector Suite (EPDS), including: • High Energy Instrument (HEI) • Low Energy Instrument (LEI) • Energetic Neutral Atoms instrument (ENA)

HEI: Relativistic Electrons, protons, heavy ions LEI: Low energy electrons ENA: Energetic Neutral Atoms

HEI: 101 -‐ 106 counts/s LEI: 106 -‐ 5x109 eV [cm2 sr s eV]-‐1 ENA: energies 5 -‐ 200keV, fluxes 102 -‐ 2*106 [cm2 sr s]-‐1

HEI: accuracy ≤ 20% LEI: accuracy ≤20 % for electron energy fluxes above 106 eV [cm2 sr s eV]-‐1 ENA: Energy resolution of at least 15 keV, flux to better than 20% for fluxes above 2000 [cm2 sr s]-‐1

Ion Mass Spectrometer (IMS) & Neutral Mass Spectrometer (NMS)

Ion Composition (IMS) Neutral Composition (NMS) Relative Density

Mass Range: 1-‐50 amu Ions: H+, He+, N+, O+, NO+, O2

+, CO2+

Neutrals: H, He, N, O, N2, NO, CO2 Density Dynamic Range: Ions: ~102 to 106 /cm3 Neutrals: ~104 to 1014 /cm3

Temperature Range: 200-‐2000K

Mass resolution accuracy M/dM: ~30 Mass resolution sensitivity: 1 amu Relative density resolution accuracy: 1-‐10% (TBD) Relative Density resolution: 1%

Electric Field Instrument (EFI) Electric field Preamp Voltage

±2 V/m ±16 V (for 8m probe-‐to-‐probe separation)

TBD: Requirements will be defined via ionospheric modelling as part of the initial phases of the mission definition

Langmuir Probe (LP) Plasma Density Electron temperature

100-‐5x106 per ccm 200-‐50,000K (0.02-‐5eV)

Accuracy ≤ 5% Accuracy ≤ 20% or 200 K

Magnetometer (MAG) Magnetic fields 15000-‐65000 nT Accuracy ≤ 2 nT, Sensitivity 10 pT/√Hz at 1 Hz

Cleanness ≤ 0.1 nT

GNSS Receiver (GNSS) Total Electron Content

10-‐1-‐103 TECU

10-‐3 TECU

Table 2: List of Daedalus instruments, measurements, estimated dynamic ranges, accuracies and sensitivities.


44

Figures

5

Figure 1: Simulated orbits of the main Daedalus satellite (green) and of a deployed sub-satellite (red).


45

Figure 2: Overview of main processes affecting momentum and energy transport and distribution in the LTI.


46

Figure 3: Discrepancies between global integrated Joule heating as estimated by (a) SuperDARN and Polar measurements, (b) AE- and Kp-based proxies, and (c) AMIE procedure during a solar storm (from Palmroth et al., 2005).

5


47

Figure 4: Total Ionization Rates vs. altitude at various energies of precipitating electrons, as marked.

5


48

Figure 5: Simulated key variables in the LTI as a function of altitude: Temperature at quiet and active solar conditions (left), neutral (center) and ion (right) constituents. The altitude range from 100 to 200 km shows the largest rates of change in most variables. 5


49

5

Figure 6: Simulated Daedalus lifetimes as a function of launch date, for a perigee of 150 km and for various values of apogee and spacecraft mass, as marked. It is noted that higher mass and apogee lead to longer lifetimes, whereas higher levels of solar activity lead to shorter lifetimes. Solar activity is plotted in terms of daily (grey crosses) and average (grey lines) values of the F10.7 index. 10


50

Figure 7: Joule heating from TIE-GCM (left) and GUMICS (right) for the storm of April 6th, 2000 (from Sarris et al., 2013)


51

Figure 8: Simulations of Meridional and Zonal winds and ground track of a spacecraft orbit


52

Figure 9: Schematic of the main phases of the perigee history for the Daedalus main satellite (gray lines) and four sub-satellites (magenta lines). The sub-satellites are released during four corresponding descents (“deep-dips”) of the main satellite down to 120 5 km.

A

B

C

Main satellite

Sub-satellites


53

Figure 10: Daedalus perigee (left) and apogee (right) history for a spacecraft launch in 2028, initial apogee at 3000 km and initial satellite mass of 400 kg (including propellant). Apogee and perigee maintenance are employed by means of propulsion.

5


54

Figure 11: Spacecraft observation geometry: Daedalus s/c with extended field booms; four electric field booms are arranged in X-formation in the along-cross-track plane and two booms are aligned vertically (left). Ram direction instrumentation (right).

5


55

Figure 12: Measurement scheme by the main s/c (green) and a released sub-satellite (red), when apogee is at high latitudes (dashed lines) and when perigee is at high latitudes (solid lines). [adapted from: Gang Lu, The Comet Program, 2007] 5


56

Figure 13: (a) Altitude vs. time for 10 Daedalus orbits; (b) altitude vs. latitude. Red dots: measurements below 500 km. (c) Horizontal sampling (d) vertical sampling of neutral temperature from NRLMSISE along 10 consecutive orbits, during the April 2000 storm. 5

(a) (b)

(c) (d)


57

Figure 14: Long term evolution of Daedalus’ Argument of Perigee, Inclination, Right Ascension of the Ascending Node and Eccentricity.

5


58

Figure 15: Time offset in the co-registration of measurements over the same location between the main s/c and the sub-satellites due to different speeds. 5


59

Figure 16: Interior of the main Daedalus satellite, including key s/c subsystems and instrumentation. A deployed CubeSat sub-satellite is also shown, with examples of potential sub-satellite miniaturized instrumentation. 5


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